{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# _*_ coding: utf-8 _*_\n",
    "\n",
    "from snownlp import SnowNLP\n",
    "import jieba\n",
    "import sys\n",
    "import matplotlib.pyplot as plt\n",
    "from wordcloud import WordCloud"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "outputs": [],
   "source": [
    "con = [\n",
    "    \"哇太好看啦\"\n",
    "    ,\"少爷好忙鸭。这个少女前线嘉年华是五月三号的，少爷在上海那边。五月四号是深圳初空动漫无限幻想嘉年华，应该是一晚上飞过去的[笑哭]我昨天也在深圳的无限幻想嘉年华，看到了少爷昨天也算在漫展呆了一天，于是合了影签了名[星星眼]这期新视频出来的时候，少爷估计八九不离十又飞回上海去了吧[笑哭]\"\n",
    "    ,\"视永兄[脱单doge]\"\n",
    "    ,\"来了！这里是帕斯卡！居然有三个镜头，少爷太给面子了\"\n",
    "    ,\"这个人已经变成了六道的形状了\"\n",
    "    ,\"牛蛙牛蛙牛蛙牛蛙牛蛙牛蛙牛蛙\"\n",
    "    ,\"建议改名：御三嫂再聚首\"\n",
    "]\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "outputs": [
    {
     "data": {
      "text/plain": "'少爷 好 忙 鸭 。 这个 少女 前线 嘉年华 是 五月 三号 的 ， 少爷 在 上海 那边 。 五月 四号 是 深圳 初空 动漫 无限 幻想 嘉年华 ， 应该 是 一 晚上 飞过去 的 [ 笑 哭 ] 我 昨天 也 在 深圳 的 无限 幻想 嘉年华 ， 看到 了 少爷 昨天 也 算 在 漫展 呆 了 一天 ， 于是 合 了 影签 了 名 [ 星星 眼 ] 这期 新 视频 出来 的 时候 ， 少爷 估计 八九不离十 又 飞回 上海 去 了 吧 [ 笑 哭 ]'"
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cut = jieba.cut(con[1],cut_all=False)\n",
    "res = u\" \".join(cut)\n",
    "res\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "outputs": [],
   "source": [
    "def getWC(text):\n",
    "    mwc = WordCloud(font_path='simfang.ttf').generate(text)\n",
    "    plt.imshow(mwc)\n",
    "    print(len(mwc.layout_))\n",
    "    plt.axis(\"off\")\n",
    "    plt.show()"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "outputs": [],
   "source": [
    "content = \"\"\n",
    "\n",
    "\n",
    "for c in con:\n",
    "    cut = jieba.cut(c, cut_all=False)\n",
    "\n",
    "    content += \" \" + \" \".join(cut)  + \" \""
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
      "image/png": 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y0wJMohWHlItJsGIWrcjC6Gda0ePE9Sh5hvL3HukKskzRxg/QveVllOC585VMF2ZzNtGoj3DYg9WaRzjsobBoBZ0doz/YPu8pqqvfn7IPk3nslFUQBQRZQosPW+SS1YQ6whXjuGAO/XuH3SDlK/MoXOjm3Yfqxh2vbJKQjOJQIkNulYMPPnQZnno/P1n/HLFAAluumU88fRX7n2hg2/1HRvlRDz1zmkPPnKbmqlK+uO1Gfn3dX/C3pSd3E2WRtZ+dj6vcjj3XQsnynDEW6vp7F9F5pI937jtMz6n+oaSJwcSMaP/4GYxnDVGk7LqP0PnOCxicbowON86a5dQ/9D3ifi+R7laMzpxkU6OZko13EPG0YS+r5tSjPyLak4bPdAKoiSgH3vjxhG0MJhsrr/sGp2qfpuv0TgDW3Px9al/9r5S+16liZCBtEO31mymoXDWmndnmwl28kNZjr9PduHvcPgtnrxk3iWI8rMm6EUgqF8JagB6lBYeUS0KPYROdrMq6njf9fxxznFGwYJOc2CUXWaKLLMlNtpxMdY/rEbxKJ4fCmydMWrCIdlbYrsIuuQDoV3uJaqGBxIcwMS1Mv9pDiXEuMT1CgaGCd4MvTen6povMk64gUnrDR8mqWoi1pJLeve8kg2+6hq5poOvJG0JVk781LZniqWnomjrQRkvKx/TBbQN/j2ivq0qyrxHttURsytaBLJtZvuIznKh7nkQ8jMGQnOadSbiQdP4LgojDUT62nxSBtLybV+HfVU+stTcpe9LBdelCel4e7jv74nmjSLe1tpeaq8pY/4VF7H20nrB3rP65ZmMp9jwzux5MEvNt96+nZY+HF766a2gqH+qJcuL1NlZ/ah6FC1089ffb0JTRD2Ldq61o39OJBdO3dDVF4+DTp7n1pxeTW+WgdW8PbQd66DzSxwV3V5M/18lLX3s35bGDhWuU6MwlOyT6+9CUOH1Hhsdgzi1CMtvA70UNh5AGLN24z4OuazQ98wDG7Fyq7v4SobbTeHa9Trj99HinOGtkF84DQcA3IrXW33MqI4QLjOs2UOLhMe3C/V10Ne6mZtWHOfDGj9DUsfeCIIgUV2+YMukei+ygO9FMdIRSYYFlLSbBwgLrOo6GUwdyL3XeiYCIosfxKd30qV0cjewgrPWj6undqxEtyK7gC1hFB6FxjnNKeRgEE7Wh15hnWUOhoZLOxMx974PIOOmacvKxFCcL1RjdeRRtvDXTp5gQWiJOor+PWG8XodN19B2Y+EaZv+B2NE2ht/c4+fmLMIzxrY1GIhGmqvraMdtHkq4x34khJwvFH0a2mYkBhbevo/PxbRjcWUPtnGtqsM4d7a7QFI3X/mMf/7T3Vi78cDUHnznN7odP0D8ioWDulSVs/1VSamTLNXNqcwevfbd2SOc8iO7jSdfIsZebxxDuIF74yk7iUyBdSNZDeOSjb1GyPIfTW4ezy5Z+YHbqINkAZLMM+uhg4ExAjUWRTBbUWFJ3qURCSJYB9YuuoSUGFDDhILI1KU+K+3qoe+DbuJaspfz6jxLt6aRr64tEujKTbz8SeWXLCXibiEWGXVfTmb6PDwHQEERpVO0Gg2lsYShd1wj7O/B11VG24CqaDo219srmb8Rsn7qcL6j2jSJcAEkwYJWcdEWbxiW47YFnh44/Gyh6ImVW3CDyDGXE9Qg+pZvjkZ0stl7yt0m6sZ5OGh78AaU3fhRr6Wz6arfTf+JAMpIpigiiCIKIIEnD2wQh+VuSB7YJCEKyrSDJA7UeBo4befzg3wNvdoPThdGVhyknH1NOAY65SyYk3fLyDShKhD27fwYkCdUgj1OxbADxWIBDh/4wZvuatV8d+luymZn1peuJtvbSu6k2uc1hAUFANMoIskT+TRehhmPU/f1vUp7n6Xu3ccMPVrPiziqW3TaHn13yPLFgAqNVpmC+i67jPqxuE7fdv56HbnstZR+DkrFQ7/gP9Ik3phcpjocSowgXQJQE1HHIHUA2SyTOgSxMDQeRrPYh0lUjQWTz8Mt0UDKmhAMIkjxE0GosSs/uN+mtfQf3krXMuuUz1P/uu6ixzKo8svPncqp2tPJmOoVtxoMgJJMjFq7/LPXvPkos4htIgMgZ2WjgxMmXZPPRV1h+1Zfpadk/Kn04r3wFpfOvSE+qdgZSScYkwUBEC3AyOn4NlLMl23RRaJxNd6IZHZ0+pRO/OjYbciYwIz5dJRTAu28r1tLZyRzwpulkagmIBgNaYmr+P0vRLCo/fC8Anu2vTth/LNZPc/Nw9D+RCGOx5iBJJqqqrqGr6wA+3+g3Xyye2kctjahVGjndRfBgE93P78a+IKmjjXf4yLl6GYY8BwUfWEPPploU3/h+1NPbOnnyc1u49ecXY7IbhqzD2RuKaD/Qi8Vh5KYfruWd+w5N+HkkL/XcpHSJkoieQoM7CJNNPquCOulCiYSQLXbifcmHSImGhyxdADWS/Nx1VUWNhpGtWUMEDaArCr37km4x95K1eHa/mdHxqWqCnpbR2WFaBkkXkuoFT/Nell75j9Tvfgy7u5yRqX3CUIWz5PelJqI0H9lE1QW3c/DN+9B1jdyyZcxZ8QFOH3iBjlOptfUTjiKFZEwWDMS16IQZYucKNtHJwdiwFPVE5F3Mom1MQkemMWPqhVBj0t9om1Wdcv+sOz+PweHi5K//Y8y+nAsvoeDyG2l74Y/4j6UfJXSvWE/hlTfj2f4qnq2bJmmt09U1+sYPhz3k5M5DVWPU1T1LWfnFzF9wO/trHyASSfrbgoH2lL3FYv0YjXbi8YHplCgSbfJQeNd6HBfMRg3H8LywB3OJm97XDpB/8yoiDV30bT4y7gjbDvTyk4ufo2iRGzWhYTBLvO+bF/Lgra8S8cd59GNvjXtsKthyzNjyzGTlW8gqtOIosjJnfRGucjub7zvE3kfOLo1ZMooTug6yy+34Wmb2hgaI9XZizi0c8svGvN2Y3Pmj9g8i6mnHnFdMrG9YOmfMzqVk4+20vfY4cd/409PpoLj6Eva/+gNUZbSvXk1kLgVVEJIlHbtO76K7aQ+LL/07rM4i9r/2PyPajE5SAOhu3E3I185FN3yHkK+Vup1/YOezX5v2OKQU9GISrIQ0X4rWqWEW7TgkN6XGGpxyHkYhKdkMqF62B1KkjKeJLMnN/tCbo9wPES3IZc4PUht6HZ+SOSnlmZgx0lWjEdRoBKPTnXK/tbRy3KCXGk36L+Us55TOmb/+Grx730mDcFMjkRgOpAG0NG8lHguydNkn2Lf3V8TjAeLjFLVJJMIYRpBu+8NJQlT7wzT+YhPGfCfuKxajBKOIRpn2B9/EuaYG56q5+HedmHBcHYeThF95cSGhnuikSgOzw0jREjelK5J+uKv+dQWSQcSWO1ZLrGs6EX+c5bfPJhFROPj09H1aoiRM6NO1ZJtoq80siaWCEg4iWexD/yfdCxXD+yMhJLMNNRpCCQeQbcN+dslsxb1kDU3P/jYZmM0gRMlASc0ltNdvHrMvo5auMFx7QddUTrz7KM7c2QMpvSPawJhnMORrw9O8l9MHnjtrl4c4jqWb0CeevS61XZbUxYrZyEJyBtmrtNMeP0VA7SWo+gifZQZZjeUi9gTH8sTJaC3zLKvZGZi5NPEZ1enGfT1YClMvmRPpaMFaUoFsy0IJjc4GiXYlfUoGh2tK5wucOkLnG89Nb7BAIhEaRboAXV370dFYtPhD7K/9TVI/mQJKIoLJmEWI5I096DrwvnEIyW5GDcXwPL8H27wStFgCQRLx76jDddmitMdXc2UpTbuSmkZBFLjgQ9UULXJhyTZhdhixuIxYXaYxS+Y4Cq146v3UPn6KUG+UsDdGpC9GuC9GX0twuqn1YyDIYsoUX0ha2QazlLY07WygRIKYcoZX01BHBNIg+VKf99lv0H/yEJLFjmwbXTejc8uLZ6eRHQdlC65CEFI/cqlUA6mQTpaYwHAaMEA02EM02JOybapaIs1H/kLh7LV0nNyS1pjGg0W0k2coH5B+uQlrfmTBSEKb2KrvSbThlovoSjQRVL0EVG9Gp/y5cik5cmoddWusjlmmhRQbq2ifgTKTMMOkm/D1jku60c5mrCUVGLNzxpBurK8bdH1cKzkVbOVVtL/8J6bLIGazK1nhX7bAGTdtd9dBBASq595A/YkXUh6vKBFM5qRlnnvdBZiKXXhfP0j2xfNHr6whiThWVtHxyDuogQh9b4+tzjYeZq8vYtM39wBJC3XvI/Ws/uQ8Lv67hQS7I/jbw7TV9hL0RFj5keGC1fseO0nNVaXseGD8OhWZQNLS1cZsK5jvGtLyznTNXgDJZCGrcgGSxYYoyRjsTozuAqzFlYTbT6NGQpx69D6y56/AVjoHc24Rnl2voSXiQ7OsTMPqLKK4ekOK8opJpGtVGky2yVNzBWHSlTaG3Qtj2ynxCLMWXYu/u360dTxFVJkvSJ4DjagWRlIlZMFAbJJqXm3xE7TFJ579TReyYGSh9WJax+lfR6M+spv5lrV0JRpR9cwHfmfY0h1/KhntTkZDDdm50NY4ap+uKCQCvuS+NKEl4mc1HSotXYPNVoCqJliz9iv09h7nRN2w1dzVdQCz2UVe3gK6usYWKVGUKFZr0m/Y+0otjgvmYMjJwvP8u+jqgJ5Y1dAUFbTk/4IojJF5TQSjVaZ593CEVdd0djxwjH1/OjkqQCUZRFZ+ZC6hnii2XDMN2zqRTGKSFCcIdJ0tRFFAGXAvmB1Glt5aydLbZtOwtZOOg0kXSWbq9o4PZ80yjM4ceva8iRaPoWsqxuxc4vs2D/l4lWiYqKeNTk8b/rpaRKN5ygHbqUAQJaouuB1/dz3dTXtStknX0k0v3Xy00ZC6yWBQbXS7QZlZyNdG9cq7OPjWT6b9XLXFT1Af3TuUYisgsjH7YylTbs8V5lvWoKFyfIKqYl2JJipMi5ltWkr9BCqL6WLG3QvjYTCYMTLAMerYvp6k3zdNRDqapza4M3Dy5MtA0gJwu6upnH0VJSWraWvbOdSmqeltZs+5GlKRrhoj0J/UdOqKhn9XPa7186n+wUfp33MSpT+CIAgIUlISh5j821yay8l/eSStMXaf8KVcEudMRcCGLy6mtbaHoy81c9W/rgDg7f85yIZ7F/P2jzK3QsGZEGQBTdXY+LXlLLx+Fo07unjy81vxNga4/MtLQYfuOv/kHZ0F/HX78ddNXAh7pFJhJnS4Z2L2spswmGwc25ZaHggDS+ykAZPNlVbthXTdIyPdCyVzL0XXddrrN9Ow/2mWXP5FyhZcRfPhqZf/jGgBEnpsFMHqaIRUH6FzWNFrJMpM8yk0VLIr+OKkFuyJ6B4utL2P1viJCWv8TgczSrqhxvGnCJH2JtRICHvVArq3vDxmf7jl1LjKh5mErmv09tbR25s6DbfhVOqFMBtPvzFmW9+WY/RtSU7pnavmovhChOqmp4udfXEhW342vtIBwFVu50N/uBxREvjJxc+x6IaKoX3xsIIgCdy79UZ+f9cb+FqmXz1qFASovrSY1Z+aj6vMnkzu+G4tr323dlSzJbdUcvQvzePWeZhJC/xMJALnRgcKsOqG73B8x8Oc2jdxRbx0kVOyZIzc7EwIopS+e0HTWLj+M0TDfZza+ySDlm/I187uF7/Fiqu/SkHFKg5v/gWRQPoR/Xf6n0i5fVvg6bT7yCSucH6EE5F3ec3/UFrt+5ROdgVfYIPjdl7x/TajY5nRWnqJgC9l/d1BxH29mFx5pFoaINF/7h6McwH/rhPTJlyAuRtLad03vnjb6jbxgV+sx2iVee6fUk+dtvz0MCFPlBv/Z82YYNt0IJskPv7kVdz0o7U4iqy89t1aHrw1daKGwSLTPEFFM7Pz3BUM0hPxoVTgmURu6VKObv0Nfs/kARm7K3Xs40w486pS6l9HQjKYmcy9MNiHyeoiEQ9zat+TY45R4mFajr2OwWRj8WVfwJKVl9YYzwZSioSKs0WuXEpdZBct8amtl9iv9tKdaMKU4RWKZ7aAqa6T8PciSKk/yISvF0E2YHCOVSn8byPds4EoCVRfWjzuirgGs8StP70YR6GF57+8c9xyjUpM5eWv7yavysGV/7xs2uPJm+vk0i8t4Z5Xr8NVZmfXg3U8cP1f2P/EqQl91L5CUxoAACAASURBVOONy5JtomihmwwuiDshdFVFjWdWDjYaAmXzN1I6f2PapRHzyldQMvfSlKm6ACZrNiU1lyEbLbhLJla8ZOdXT2rpWrKSbr3Zy2+mfvdj47ojuhp2EI/4kQ0Wll/1FVa+/+vMX/cJbNmpq+2dLSxi1uSNpoASYzVLbJfSGh+/gNREOBWtZbntyowS74yXdoz7ejE43EPZQaP2+ZPBFVNOAQn/6GIficDM+v7OFeRsG44LZuN9I43MsUGcEQcpvyh/Qkvw+v9aTf68bJ7/8k5Ovp06eWMQHYe8vPvwCVZ9vIa2/b0ceq4x7WGt+sQ8Fl5fTk7lsMQq3QplPaf66e9MHUDJneOYNLEik9A1dUYkYZCUdM1ZcSuJaJCDb96X9nGBnkZmLb6OWYuvQ1WGg3qCICCI0pBlGg32YLbljNfNQPq8lCwINUGb8gVXAxDqa5swUKZpCvV7HsfqKCQe8aMqMVQlRiyUeaNIFgzkGlJLuaYKEYn51tU4pYKzqh7Wr/bilPJYn3UbHqUFv9JNRAuS0OP4VU/aBXhGYuZIVxCwV9RgcGRTfusnUaMRdFVBV1U0VUGLRzG6ktOV3FWXYy2bQ7y3i7jfS7yvByX4v4N09YSKdW7xlEj3si8t4a3/GQ54zb1y/BtRMopUrivkxX/eRf2b6bkvtt1/hKpLi7jya8unRLqHnj1N2YV55FQ66O8M89q/70uLcEuW5nDsL+MHOlv2emjc0UVe9dSSYaYLXZsZkzp/1oXkli+n7fhbabkURuLwO/djd5VituchisMzQ13X0DQFNRElHg1MWgNB1zUaap+hcukNE7aJBD2YbC6Obf/dpGPzd9ePu6RPJiELJiQMkzecBA4pl4XWi+lTOtkZeG6ofu/ZQEfHIeVgEe3EtQhBzU9Q7UNl6qQrTDQNEQRhyuaAwenGUlCKEg6gRqNo8ShqNDJQmlFPRlYFEdFoQjQYEA0mRIMR0WTG4HAh2x0Y7E4MThemvOKhKlC6qhJsOIr/6D4CJ49M+CafDsxmF6tWfwkQiMf6iSeChEJdxGL9Az9+opE+IhEvmjbxB138scswFmSj9CWDVfbFswgeGjvNFEwGtHCMtt+ODcJ9cftNRP1x9v+5gQ33LqL9YC+PfGQ47ddoM3Drz9bhKrPziytfTDmORTdUcM23L+TJv9vK6W1j9ZYb/2UF864u5Y3/3E/9G22j1lTLFJzFNj757NX88KLJAyhlF+alXIL9k89ezW9vSh3API//XRAQz2pdtHNVnnEy6Lo+bsGTjFu6Cb93jKtg1GAGfmvx9Co3ZVUtxFZRg71iLlnVi8mqXowaDnLqd/+FEs5QBB6IRvs4fOgRaubdzMmTLyEbLFiteZjN2TgcpZhMTkymbGTZiNd7klCom2Cgnf7+FsLhHkb6A/rePkKkcdh/WXrPVbT+emyASZAlZn/j9pTj2fSNPdzwg9VsuDfpvxtJRs4SGzf/eC0Af7h7+sVYtv78CMtum811/3ER+nd0fK0hAp1hfK0h3vjP/RmZ7m+4dxFKPL1+UhHueUwN2Y5Z+Pub0QGbNQ+3cw5e/ylC4eT9WF1xNfWNY19gVnMOOdlVtHTuAqCy9BJ8gWb6/OeWwM52Icr3AuFOhvf8cj2Bk0cInExKpYzuPJwLLsA5fznV9/wbvXveoWfXG2gZKr3X39+CLFvweMaXZsmyhZzcedjthRQWLqd67g1oWoITdc/S23scTVNHES6AGowiZ9tQfCFEixEtkvTZuS5dSOv9qetE1L3Wyt5H6rngQ0nZXMu+pOa5fGUeN/z3Gpp2dvHKt/eOG1wDJvVbjtT8RvvjxIIJIv443XW+jEi4iha5mXd1Ga98J/MC83MOQcBizSESGl97/l6A1ZxDScFKEokQoYiHPPc8PN7hZd5j8dSGSrajfCAbMwmzyUm0J/3CNOeRPt7zpDsSca8Hz9ZNeLZuYtadnyd39RW4lq2h6+0X8B3cddb9JxIhdF3BYLANrZN2JhQlQldnLYOrOgmCgMNRxuIlH0HXdeqOP0NPz9FRxyR6ApjLcjAsmUWiLzTkagjXtRNrHz8gsfnHhyhfmU9ulYO22l5W3FnFus8t4M0fHODIi5NHxcU0Vtd98NZX8beHSUQy666RTRLXfPtCGrZ2cPCZc299iAZTctWRDLmhLNYcapbcwf4dP89IfzMHHUUJk1DCGA32pFssloyP5Lnn09yeerWGXPc8Tre8TU52NTZrPmaTi1zXXMzGbETRQCTWN+6x5zE1/E2R7kg0/ekXWIrKKbziJorfdwfO+Stoevz+s+43HO7BbHaNS7pnQtd1/P5mQKCv7yR9fWMDDglfCOvcYnxbjxPvGrYeoi0TW01qQuOlf3mX933rQuKhBLNW5/P7u95Iq36BIApUXz55JLjn1MxkB136T0swWGRe/tfdZ1VQx1FonfIqwZLFRsUtn0GNhPDsfpOYtws1Ej6rNPFIqIdY5L0vYxQEiZ6+eqJxPzZLLjnZVYiijDOrDNARBWnM2mLOrDIUJUbVrKtoatuCP9BEQgljNbtp69pNOJqhZYTOA8hwIM1oErjmFjvZLhGnS8JgBFUFm13kwZ/6aG8Z3+r40UMFeHtVPJ0q3R0Kl19r4x8/1kUint4QJIuNmr//Np6tr0xSvHxiVFZeSZajFLe7Cp+vkUCgDZ/vNL6+BlQ1dX7+ggV3cPTo42O2V3z5Jvq2JjPSspbMInikBdEoY1tYRriuHe+bh9CVmZNJrbiriiu+uow/37OFxp3nbsXVL7x9PS98dVdGlnc3WGQ+/uRGfn3d1FJRZZuDeZ/9Bkd+/GV0TUM0mpEtViSzDclsxeTKQzJbyZqziFhvJ7LVjqWgDMliRYmEiPd56Nq+iULbPLo7DiAKIhU113Bg5/3MmX89LQ1vI4oGispXc7oumVFpMNpwZJfjyquht+sIfT31WGx56LpK2exLqT+cOphYcNfddP3pkbOWsQmChCybMMhWTAY7VksuZpMTk9HJqebXiMUDVFdczcmm10al/5qMWcTiAazmHKyWXNzOSuqbXkXXtaSbITZ1JZEhL5+EZ/Lvv/Lr/06ksYHel18g0fO/x6d/zgJp8ZjOkdoYXR0KRSUy1QuMvPRkesGu5oYEv/wfH6XlMn1elflLTGkTLiTL93W+/gwFl96AbHfS8dpTTEdtH432YbMXsm3r98jNnU+Wo4SKiiuwLfwgfX0n6e4+RFfncIqrwWCjs7M2ZV9aNI5/R1KUbV9cTriujbinn6ylFXjfOIiuzmw2QO3jp1hwXfnMrr57Buz5Fv7y9T0ZIVyARESZlqpCjSTvO8liRwn1o8WjxONRGAjyBpvqMGRlk3PBJZx65IdDxzlrlqFGw4TbGtGUOFpNNQFfUu4WjybJJxzsJh5L5uOraowsZxnB/jYS8RC9nuPkFi5JEq41h0homEjMVjfR8FirMbB/H4Uf+ihdjz+KPs3CO86sUgpzl5JQIkRjPuKJEL2+k4iCOGSp5rpqUgbRYvHktWi6Sq5rLscbXmR22aU0tW+fFuEKkoTjojX0vjR5mdXWn/2Qgrs/Ttk/foX+HdvwvvEKWiRzBd3fi8h4RtrJ43EC/qmTSVGZzN991cXKi82UlE9Pq+fdt5XTf7wP+5z5lLz/g9NapiYa85NlLyaRCNHRsYcTdc+xd8/P2b7tu3R27MXtrmL+gtuwZyUzchKJEF5v6hoTomU4oSHS0IWxMLlMe6zThyE3s5k3qaBrOs/90w66685dQGTJLZWcemf6y5gL8tjsxT2/n3qZP13TUKPRIclhKiSCfgRBHCpiLggiJRvvINbbhTaQoDBItCMRG7EtHu3HbHWj6xpOdyWFJRfS3ZZc7cRkycadV4M7rwZfz8kxq0UMIlx3HNuiJZR87u+RndlTvlYAf6CVutMv4Q80486egzt7NpWll1Bd8T4ACnIWJRMtEMjPWTDmeKPBTmXpJZxo3ATodHj2M6f8cizmqdW0BrDMrSHrggsR5MltuoTXS9v9PyF4oBbnxRso//LXQJzZRNm/Nt4zV9fVpvDz/+xj6+sRJAnyi6RpLe0V7W7j9B9+jNGVR/H7UsuxJkI8HsRscWE0jn5YFSWKx3OEY0f/TG9PHTU1N7J02Sew2QvH7UuLK5TeczWln9mIdXYB2WtqKP3MRmSnldJ7rsZx4Zwpjw9gVkX6+emBrsg5LSaz/ZdHJ280AFPZ2Fx++8qaMdumksAxEkokgGyZYKFRXSfe70UyWQf+1dA1BWnEIpYmyzAJGgbuCYttuOSoxZpDsH84KaWn6zB9vUm/fjjoweupw+upI9jfNm4BfAaSNUzFJZR+4R8wlZZP7UJHXZJGV89hTpz+C929R/H6TmE02AmEOvB4jzOrZD1ZtqJRxxgNNipKN+DxHqeiZD2VpZeS555PY+s7zC67gvychVMag+vSK5GsNmyLlqQ35kSC7icepefFZxHNFsq++E9YquZOfuDfKDLqXpBkgVmzZVw5EguWmpi3yEj5bAOuHAmzRcDhFPntfT4O7Rv7xp+3xMTnv5JNb7eKp0vl0V/3Y7YIRMJTJwwl2E/TYz/HfcH6KR+rqXGamzYPr3WWAt3dB+nuPkh2diXz5t1Kn7eehoaxfuTmH6dOWjhb3HW3FU+Xxm8fyExB8IvXGzGaBN58fSbrEYxG9pUrkLKsxFqGp9+CJGJdWEFgR/rEPRGUcBDJOvGMQpAkRHl4ZqWEg4gjiuHEY0GKylahKFE0TcHuLEHXVdx58xBEkXDIQyTUgyQZcWTPoqDkAmSDhRMH/0w81k9JxXpiUR+CIBAJT75Uka5paNHpT691XaOk4AJyXTVEol76g23EE0HiieT9LAgCp5pHJ+OUFKykuX0b8USYnr46sh2zSCgRivNXcOzkMyyaeztFeUs5cPzRSc+fteJCzLMqAHBctIbg/vTXOPRvfYd4RzvFn/48xZ+6h9CRQ/S+9DwJ78wv8TQZsnKMBHoz46bLeEbaIOYvMVE+W+aVZ1MTQ5ZD5HNfcWGxCkSjOkpcZ9YcA6frE5w4Gqe3W6XPq9LeohDs12YqVX4M5lRdQ1fnfoLBDkrL1pGXtxAQOHzoDwiCyOo1X+adzd/kzJD80mUf59jRP09I1unCahUIj/Oyyc4W2fpuHldf3kNba+aCcK9vzuWr/6+fvbtn1v9rrizEcclSEh4f9uVVxLt9+P6ym1hL5hcCLL7yA1gKygi3NyJIMoKYrEsgiCKCbECNhuk7/O5QcXOAWTd9En/dfnzHpqYtFgQRV+5cQEcQRHq7p7ZKx5zvJ/3Kjd/5OmpouveQQHXFVYTCHvr8DQiCxJzyKzhS/xQu52xk2URXz/grlSyaexsNzW9QmLcMQRA53bp50uzLoTOLIkWf/hyWyuTsrel730bxp+/WKrjjQwQO1hI+dhTRaCT/jg9hW7h4aH/nw78ldGzi0qYzibu+XcPu57s4uSe9azqnGWmDEISJ41iBfo2fftdLJKxjNAlUzTNSWW2g/micE0fj2LNE3LnStPzDUx+riK5rWK25lJauoaRkDSfrX6S1ZRutLdtwueawYOEdKIkoXm89qTRQx489RfXc66k7/iyKcnaBgC980c5/fS8Z3JBk+I/vO/nFT4M0N6lce72Zp5+M0NaqYrcLlJZJXLHRzC9+GjyrF1M0Cq0tM19wJtbiofuhgWCOphOpb8O6qALb8ioix5uJnMhcUXElHCTu99LxVvqrxqrRyCj3QrrQdQ2vZ2qlA1OePzK9VRVE0UB50Wrau2sxG52IkpFQuJv27n3k5SxAUaITEi5AS8dOIjEfbV27KchdjKYlEEUDkiiTmOSeznn/TUOEGzlZPyXCFUQR29LlCEYj4WNH0eJxOv/4EO6rrsV12RUAFH70k4SOHqbnuaen1HfK86Vf430IIb9C1crstEl3IswY6UoSTBacH3QdLFhq4pKrrZw8FudDn3Xi61XRNPB0KTz6wNQLSkwNAvPm3UIo7KG5aTN1x5+hqvr9lM/aQFfXAVQ1Rl/fKYLBDi5c+QX27P5Zyl5isX7qT7yA1ZpLf3/LWY1o8RIDX/+Wg7k1MnNrZNw5Iq/8JUpzk8rtd1poblLZeygfgyzg8Wg89sfwOZsJnC1GSuTUUBSlt5++k0mfqGVuKaLJgBbLzHeuhoNIxRVTOyYWQTJZJm/4HkOWrYDmjh1omoKmxllccwd7Dv8OqyUHr6+BUGR8OVZB7iJkyYxBtpLrqgF0ZMlEVflGBFEkGvPR2rln1HLtI5F98SU4114MQOTUSToeHn+FjFQwlZUjiCLWmvmIZjNaNAq6jveVl0h4usi79Q4EScK2YBGWOdV0PfIw4RNTf8EJosBt/1pNsC/B1sfa6O9Jf1aXiKos2OBm0/2NUz7vmZgx0p3Kelwf/3snj/2mn5w8iUd+5efE0XMncaqqvpZs1xyOHXsSgP7+ViTJyM4d/83KlV8YSHwAk9mJkogwZ841aLqSrFc6UMRHR0PXVDRdxe9Pr37qROjr0+joUNm6JUb9CYWnnsvhrTdiXLHRRO2+BL/5VQiDAZoaVT7/BTu/+XVmfLvTCVxO5yTmOcWo/hDxFg8IILuykkGtrj7sK2vo33YkI6UXlXAQ2WKn4pbPkAj6SQR8xPo8RLvbiHlT65bVWATxr0i6aaxulhL+wPAMIRLzcezU81jMLtq69k3qIgiGkp9FPBGc1KI9E7aFi8m5LlnRLNp4ms6Hf4OemNpLM+uClQAIsoxt0VICe4azSwP79qD4fRR/+vMAiCYTsiv9BWtHwplvpHKZk5IaG1d+ohxPc4TuxjDdp8N0nAzRVhekoz71syQbRUrnZWVkncGMk25hiUxnm4I4iXthEBuvt/H840Hm1BgpLpOpP4eEW1q6Flk28+6uHw9ti0SSxWuMRjstLVupnnsDfn8THR17ByQ3A35BhGTt0oGqacVFF9LtOUy//+zWagNQFJ0Hfjn85Q+S4ac+a+ML9/jo7Ul+sEajwPuuM/HznyZ9gBetMvLurnP3+U0HptJcDPnZyNk2JKcNkw7GAhfRhg6QxKRkLENmuxIJItsd9B3ehWgwIluzcM5dSsG6awmcOkzf4V1Ee0bL27RYFIP93JSYnEkEQunL9iaygidDwV0fBkEgerqBjoceQItP7f6TXW6yll849H/WshWjSBeS1rPS34/sSNZxVnzTywz0dcb44Qf38p871/Plle9QtjCL/FlW8iosLLkil6vvqSDkS1D/bh9HNvfSdLB/6FZ0F5s59FZPRpRAGSfdmoVG1l5qwdOtEgpNPMCqeUayHCJPP5L0X159k43r77BzYHeMza+ESSRmbs4sCALhSA+trdtHbdd1nVDIg82WT1vbLiIRLwsXfRBZNtPaMn7ueXPT5hkZpyzD4GIM27bERxHunR+08O7OBPf8nY2aeQauv9HMh273smvne5d4Yy2eIcWC+8a1eJ/bjuOSJcQ7vcSaUlufkmBARxuTvjoZlHAwGdSq3TJmn3vpOkqvvZtodyvtbzw1tBqwGo9Oy6c7YxAEjIVFxDsmLk7/14Clcg6CLBM+cZzOPzw0KrFDkKQJl+oaRN5NtyIYhtUjojX1Z992/08o/vTnMLhzzsqnm4hq+Dpj5JRaaDzQT+OB0WnwVSuzmbfWzSd+vIhEROWJ75ygbkcfs5Y4ePr7U6uRPB4yQrqybEZRkpW+Nr+aDAQsWGri6IHxJUhzFxo5cSTOyePDX9Qrz4ZGqR0uv9bG0f0xOtszv/a8rut4e1OL7j2ewxQWrsDjOYLXW8+Wd76FxZrLmrVfoe74MwPBtOnhfWVf5GT/Lk76d07YLjdXZNlyA/E4KAmdr309i1tutbDppSgej4bfr/GPX7Zz2boefD6Nu+624uvTzopw/+2bWbjcIhUVEu1tGu3tKh0dKrV7E2x6eeJKblbZSViZWvaS97nkC69/88HkKsnjYLF7I4XWajzRRmp7XkybfGPernH9s94D2/AeSL5EjU43+WuupnXTYyQCPoyO6U1fU0F2OBFkiYR3mvULdB2lt4eij38aY2ERTd/7dsbGNl1Y5lRT+NFPIhqNnPrnLw1tFySJwo99CmvVXBAEYq3NtD/wy3GrAFqra7DWzEcN9NN2/08nlIYpfV6a/+s/MLhz0paQZeUY+Yc/LOfoFi8HXvPQ0xrB3x2n9pVuFl2Ww5sPjg1antztw2AScReb+ePXjqGpOqtvKaJhr5/Db2WmwlzapJtlKyQc9aJpCrJkGuX7yXPPp6N7dCrsRIQLcOLI5OTw5svp+yoliw01khnfZiTSS0nJqtHbwj3sr/0tixbfjffd9JdhORNdkVNUOVbhNBZwsHcTCS315/Tiq7kcPZzgRJ2CqsJvfxXi/TdYOHky+QKy2wVEUcDnS1q+ixbL7NtzdgGoTS9HOXxI4XTD1F5ykmBgXeHdNAX2c8I/vUpUE6VEt4aOUGitJs9cwfLc96dPvLqOEp38noj7vXh2vQ4k6zxn0qfrWL0OY1ERnQ9Pf0VZLR6n8+HfknfrHeTfdhc9Lz77V0uVtc5fQOGHPgZA15/+OGqfrqr079xOrLkJ1xVXYSotp+Tz99L5x4fG1GEwlZRScPdHUUNB2h+4P20inYpm945vziUcUMgtt3Dr16qxuwzYsg0k4hohX4KuhjCn9/cT9g8/N6IkUFJj5w//fHTItbDwkhx2Pz92EYDpIm3SdTlmU1l6GZGoF3+wBae9lPqmVwGBPPc8unuPjFsQZqbhWr4OQRDx7hs7jZwOYrF+GhvfGrM9EunlyJHHEEUJbZoVq5oC+ymwzCHPXMGagruo7XmRQGLsG3T1iuRNWlQscfU1Zrq6RpNSVbXMyfphcly02MAjvz+7B3H3uwk6O6ZR50BP4I22MNtxIVE1SHPwwPiNRRFBEtETCqLZiLE4B+fly+l+6JVxi//0RptJaDEMommIePd6Js/rNzhcoOsUX3ErCCKCJA3pdEXZmBzLoG538LfBiNHhYt5nv4m/bj8dbz875c9jJPREDNv8hVhmzyHScGr6/Wga3X9+jDnf/yHWuTV4nvkzoaPnVrdqX7qc/Ns/iBYO0fn7B4m2jA0ah44cInTkEPGuTnKuuR5jQSFl934Jz3PPDPlqjQVFFH3ys4gmMy2//G/i3TNTjOmJb50Yo1AQJYHFl+fyvs9XsObWIj747/PwNEXY9kQbtZs8KHGN1387Oi5TdWE2f/jq1HTXEyEt0hUEkQ5PLcFwF/5gC8X5F6CoMWyWPNzO2ZxqfuOvRrjO+Sso2ngLXW89n7E++/1N+H2NKfeFQ91UVl7J6dOvT6vvvng7qq4gCTJW2cnqgjt4rXX8Gq1ms4CiJF+5BhluvtWCyy1ywYUGCgpEfvd7F3NrZPILJD70YQv/8s8zLbFLjbbwMfIslcx3XTIh6dovnIt1UQXdD75Czgc24HnkDZSnt5J712X0PrUFLTzW8tfR6Yu1kW+ZDUCeuSJlicKRyJq9ANfi1fSfPDxifT4FTVOT6/TFo+hqst7uYN1dLR5DV1UMDheS2Urf4XfP+nMxlSSXVs+59gZaf/7jsw4S9r70HDnX3kDhRz5J8MA+ep57BjWcmRneZCi4826irc10/eFBlP6JS4IGD+4nfPwo7ve9H+eadeR/4A7Cx44gZ2dT9MnPIlltaJHIjPqqU0nCNFWnYZ8fk1XiN/cmdcuzFjtYdXMh1/5dJf9+3S5UZfR31FYXJJ7BpazSIt3i/BWIooQoGLBZk6XfVDVOZdmldPUcHloKJBXMBaVEuzIneD8TuWuuAJIKAgCLRaCoQKKhcfp+4MmWr25qevss+tYIJbw4jMklsFU9gYCAPo5QyGwGZeBSsl0iG6820dmhMX+Bge3b4jizRW68rhdfn0YacYsZQ18s+fAICGSbivDFUkfPg+8eJ1rfhuuai/Bt2k321Rfi27Sb3ic2475pHT2Pv53yOO8I0gWwya6UM4RBBBqOEmiYXjpxpHv0/eoUc1FRCGpTD+BY5s4DwFRahn3p8imlxaaCb8tm1GCQvNvuwr50BZaquTR+5+tn1eekEARyrr2B/t276HnuqbQCZJB0i/Q8/zThumPk3/FByv7xKwiynNTiRiK0/+bs619PB4HeODbnMPU1Heqn6VA/BpPIF363jBd+3EDDvuH4RN32zNYTTot027r2UFl6SdKy0AWC4S66e4+gKFFULUFB7qKx2S6CwOyPfglzfglH/+tLqTvOAPoO7KTwipsRjSYAigslNl5h5oEHgzz1aB6vvh5BEAREEbKdIvWnEqxbY+IfvtI3bZLStLML7AUSvUOke8T7ZkrCnb9AZuEiA6GQTiiY3F89K+lX+sZ3HLz5epR//1aA197OHVI0/DURU0N4Y624TaWszr+d474tNAZSE4zjkiV4n92G+6Z1eJ/dhuzKQukL0PP429hX1hDcXTfmmN7o6CnfRIQ7GWTBSJ5USkwPE9XDxLQwKqm/U5voxCxaAYGIFhy3XUoIAqIxWWlOVzO37Hugdi+B2r2YK2dT9NFPMef7P0SLx/Buehn/jq0ZXV5eNJko/vTn8Tz9BLH29FabPhPhE8cJ7HmX7A2XDW1TIxEk6wTFiGYYb/9+rCGYiGnc95FkbGrhhhwKq2y89XALbz6cWaMxbZ9uU/t2qmZtRFXjJJRIshq9YxadngOp/Zu6fk4yexL9Sc2eICUvpaVVpaJcRpYEtu+MsXVHDFWFhkaFSCR5Mz7zQuSvahWOXHwvro2NoEqSwA9+lE3d8QQej0Y0OvwQFRZJXPt+M1df/t5bqyumJq/FE20cl3ABjIVuXNdehLE4h5xb16NFki4FQZYJH2lEsltQg6P90zF1eAo93qwgXSh6nA6lIa22eVIpXrWTgOalWJ5Dm5K+bMi+bEXyD12n+/FHCB7cP53hjovo6Qbaf/1zSu/9J0SjidwbGbGVMAAAIABJREFUbsa+bAWepx4n3pWZwI8Wi52VW0QwGMi//YPYFy9F8fvwPPUEznXrsdbMp+iTn6XxO/+GGjo37pGR+MsvGpEMImoitcFy5J1eupvCzFvn5ug7mS24kxbpGg02XM7ZeH2n0HUVr/80LscsYvGkX6fP3zBKNjaISFcrBmfm5DepoASTYxAHSDee0LnoQiO/uM8FOuh6kvjzckWMRoG2dpUf/DhzS9TYZBcOYz4d4bHW2XgQRlTU1M7IIBFFqJkn874rkqTqdIp84zvJSlmSBD/8iZMffC+Ar29867awSJpWQOxsER8g3TOt0jMRa+mm7+V3scwrAx0idZOnTY96Uan/n7z3jnOrvtL/37foqkuj6X3G495tjDGYEgidQICFQFgSaggsyTebtkk2m74lu1k2CckmJCEJJbTQEwjBgMFgY2PcjW3cmPH0plHvuuX3x7U1I0/TFAPZ3/N6+WWNdKV7JV0993zOec5zJudPMFGIiLRl91Mu1yMg0Ku10WBZQGt2/LSFIEkUn3chAMF1a6edcI8h3dWJGg7lfHht9Q3UfuErhNatJfDyyENPJ4xJEq7kdlN5wy3Y6hoA6PzF3aiRMImD+3GvWEnppVdQ95VvMPCXPxPdtmV6jnUUOIss1C1007k/lnMLu+4Hc3nqPw6RjI68eulvTVI1a/qj8YJIN6smica78TirqSpfjttZjSQp+IMHKCueT39g5MpeZqDwqqQgSpOaYXVsDPtQw+RtOzL807+EWL7UXNpJEsiymWJwOgQuudDOC2umR3JT5ZzLTM8pEyJdURBHvA3gdou43YP9uOGwzk/uMt/jP37ZxYBf58nHxz72qmrxAyHdY0iqY1/UBIuM75JVCBYJW2MltpnVqOEYsc37CxpfpBpTL9o2WhbmUgUCIpqRzYtiZUGhQqqnUz2MgU7KiKMaGUJaH9VyEz1qKzqjH6vn1NVYSkpJtTRPH/mNgs5f/S/Vt92JpdgMcARJwnfuBSd8v2PBVt9AxaduznWRJQ4dQI0M5kmj27aQOHiAxn/5HuWfuA73SSvpf/bJgkb8TAY3/GgBs1Z6efQ7B9j6XC+iJLDqikqWnFvKW890s+6BDuKhLN996VQsVpFdr/h5+d5WqmY72b12eleVBZGuYegkkn4SST8OewlHOt/IPWazeily1xOKDo9uMsHCDlaQZer/7jO0Pv6rAg97EMe0ucIQT9TNWzNUVkisXKGgaZBI6CQSBsU+kQ1vpTnrdBsXnGvjpbVTH90eyw4gIOCUfcTVwtoTRWF0E/JwWOf2W/MLNu1t5o979elWPvXJApL6J6CRr3GGxJGWcQjxaL+yZoytoFD9YeK7mtGiCYovX03whc1IXifec5YRenl8S8WJdqaNhCPZ0eVWIhIusWjEVEJY9xPWxz6vJZeb4vMvBqD3jw/nTMpPFNRggK5f/6/ZsVU63Bj+g0D17Z9HkMzzPPzm+hFH92jRCL2PPkTp5VdinzmLui/+0/RG6ENQNdvJ/1y7ja6DJl/omoGuGfzk+u0sOruUz/5yMYIg8NNP70AQoHKmk/Nva2DmSV7W/GrqfipDMeGOtOb2fP1qasiI5+OR6Bg/b2Yrr6HhmtuRHC4WfG1wVpWWTpIZ6CNycDeZgV7SA71kwoFhSx09kz7qDGVDsQjohsG6N1J88fNuvvV987hKS0Ru/rQLl0vg4T8m+N3hGIIAJy9X2LpjalGTRTQNr8+sugF/qo1t/c+Om3OUhMExPiM1R+x5Z5C0ZBm+8GUXxT6Rq68Ynlvq7dGpqpZyeV+vV+CmW53s2J5P3CtWKnzn+278/TqhkE44ZBCN6vT26sRjBnf/OEbTTImqapEBv04yYZBKGSSTBqrK+ITL4MVEFMY+rSIbBouux7rStHCc0MvbEO3WXI73g4KORkibXMRlnzWH6s/cAUBs145J+wRMFGo4RNtdP0Ryuan+7J0o5RXvy36HQqmqpvLvbzCHUgYG6PnDfeNKwmK7thPbZeb/XUuWUXr5VfjOvYD43nfwP/8n1ODUlQO+KhvfOWfjsPv3vj7AjKUeXr63lZfvzSfW3uYEu17u55+eOHnY86aKKbcBV5Uto7t/5HxVNjZ+W2iqr5PmB39Cw7V3ENi+AcVXiuIrw1pcjr2qHnt1Q25bQ1NJB/qGkHEf6WAfeiaNIFv44Q+8FHlF+vp1in0iP/x+kWkxqZnm31u3Z/jZXT7u+McAhsGUCRfAJQ/mrEtt9cz0nMLhyOYxnpGfUhgralt9hsJNtzh5+A8JXn9tZCL63rci/Ob3RVgsAoZhtgz39ekoikBmyGDPbVsyXH7JiXXgF4/mqo1JDAQ9hhNNuCVSFW7Rh2qoHCvJCQiIgoRqZOhShzcwSBQ2HklUFMquvBqA7MAA/U8/MY1HPgqOM4fVYlG67r2Hmts/d+L3PQTe006n5GOX59J8HXffhZ6e2HcZ272TZPNhGr/1A5wLF+OYO5/QG68RWrd2wkY6QxHsHnlF6+9IUr/Yw8YnRzcH0vXpXzZOmXStyujjUAxVRStg9Eg2EiR+5BCR/TtR49Hc/YIk4WpagLW4DKW4DMVXjlJchq2sGs+8ZUd3Yn4omaCfr34zhGFAVaWE3SYwENApKRaJRHUGAub0iRfWSGNOZpgovNbBGWl9yWaao1vHfc7Q9MJopLt8hYXKKok7PxvM6XRHwuHDKpdd9MGPM4HB9zVWrvODRkDrYUCb2OBMERmtgPdUctkVWEpKMTSN3kf/MKrnwHSh6OxzQVUJbcg3W9KiEbrufX80sLK3iPKrP4l9tjnTTE8m6X/miQkT7jFosRi9jz1E2eVXIdrt+D56Pp6Vqzjywx9Me5om2JWmevbYhbJ4cPqbjSZFutUVK+jqNXNv2jiaVTVemFIgGwsjuzx5pGtoGtFD7xA9bltRseGetRCl2IyIPfOWIVosuQv+9dc6sVrNCHfrjgxnnW6ltETi698O0d2j8Z1vePm3H4Wn/B3KohXvUb1tUo2wa+DFgvKN4pDIaTSC2rEty45tJ767zO0WiEan5wJ0TJUxHTnXE4XJyM061MKmEXtWngqA/09Pke6YusXneBAEAedJJw8jXWDK0xUKRd2Xv5abKZc4uJ/+px6f8r5jO7eTfO8w5Vdfi2PufCS3h/ovf53g2peI7dqBMU3ku+uVfl5/aGwN7l9/cWRa9jUUBZOuJCm5Vl9ZHMxJjtcocEzSNR7UWATZ6QHGF2DrmRThfUcLLoLAgnlL8wppd909uM9bb3TxnX8NU1Yq8qXPufntAzEeeCTOp69z8sDDU9MHltrqc0RzILxh3ALSMQgFphdOJJxOgXjcwOMRiUY1GhskbDaB/Qcm3/iRi3Q/BKRrk9z4rNV4lDIOhDac8P1JLnPFF97wBpG3x3aQmy7Ym2Zhra55X/Z1PCylZZRdcTWi1YYWi+F//tkpd9vlXru4GNHpovu+e/Gccioll16BpbSM8muvp/iCS4hseYtk82HS7W1m04koIloURIcdS3EJyfcK01IHOsdfibS+M33y0mMomHQ9rhqCYXOAX/6PauzIIe3vRrTaxl1qpXracc1cQKx5gsYShoEai47qgfq7B0y5Vb9f5wf/OZhjfuDhqXWVyYLC4uILcn/3JAq3e5SHFNLUUVzGRoIgiHgs5ZTYaqlyzCWQ6uBAeMOkSO66ax389vdxZjbJNDZI9PTqUyJcMN3GYHokXWNBQKTWuQi3UorbYv6ziNZRt691LmLnwAvj6ocni5JLLqPorHNo+e43T3hK4Riqb70jt6Sf1NCvScC1eCnFF1+Wk6Ylmw/nWTtOBySni/qvfQsAPZWi63e/ouU736Di+htxLV6K7PNRfMHFw56nxaIkW5oJfoAyuUJRMOlaFU/utjQk0h0PajyG7HCRGedkNNMLY4/LHg1aOoX8PrcUVjpmIx2t0qcnKNYvNCKUBAsuSwluSykepYxa58K8fLDbUkqRtYpNvY8VvO+iIhFJgmTKoKJcZM5smVdfS9Pbp+F0mpKv8cznR8OxCH6qka4kyFglFzbJhU124VNqcMiD55/LUsyi4nPHfR3NyJLW4kSzA1TaZxHLDuR1tk0HXIuXUnTWOWQH/O8b4XpWrR4kXMDW0EjqSMsYz5g6bPWNVFx/IwDZ/j4G/vo88X1jD7ocBkFAcjqRvUXIXi+ytwhrXYP5d1ERsrcoT28v2mwUnXUOvQ8/QO8jD8InP4Vr6fLc47F3dpFqPkzyvcMnzKnsRKBg0lUsg6QWS/TkJugKwujm02DqaJ31s9FSyTH9brVk/Gh6YeLQMykET1FB286eKfOxi+xceJ6Ni6+c/JiSWtei3O32+DsTeu5IBSeLaMMp+3BafLgsJVTaZ2GXx/88vEoFFfaZ9CYLsw089VSFYp+IqhqcfbaVFSssxOJGzuRHFAWeejqZp3wAmOVZVYAqw3xfE1EviIJEk2clDsmLVXLgUcpzMrxCoOppEmqYhBomqUUIpDpIahFSWnxCq4jJQCmvoOwTn0SNROj+3cQ15pPaZ1U1pZd+PPe3GomcUMJVKqsoPu9CnIuWkOnrJfjaK8R27Ri1qCXa7chuD9aaWiS3B9njRfJ4kL1erLX1Oe3ueNAzGfqffnwwZWEY9D/1RwxNI93eOiGilWRhmHPYB4mCSberdzBfMxAazJlIomWkzXPQknFqr7iJqgs/gRqLkOrrJNXXRXjvVtKB/rxBarJzcpGunkkjHh35UVYq0j+GAcyh91R++oso1VUSVkUgnZn4l+FVKihSTNWCgUFHrPArvkP2DupZkVhUfB7l9iYUcfI+FfN9H8Ei2uiIj++v+uKL+dGYLAk89sfxI/WZ3lV0Jt4ds9tMLKCQ1uQ5mZ7EodyUCd3Q8CdbWVH28VHJVtXTZPQkDtm8sKa1ODv8fyGhhsjoH4yZt+RyUXXzbaBqdP/u15OfDDFBVN1wK4LFXGlmurvovu83J2Q/ObJduNicAtHVScfPfwyGga1hBvZZsxHtdpSyciSnC8nlQnK58yLVcWEYpDs7UMMh1EgYLRJGDYcpv+bvyfb2DMsR65kMfY8/MqH3UVJr4857l/KvF48eMNjdMidfWkHjUg+KTaLrUIx31vrp2B+b0L4KRcGfkKqNvHSKxnvGtCZUk3ES7e+hpVNYSytxzZiHq2k+paeei6GqpP09pPpNIp5KpAsC8+ZaeOh3Jbz0SgoD06LRMEASBWx2gUcfj7Nlm5lvDAR1bLbJkW6De1nudn+yhZQ2+OVIggWr5MQmOfEqlbklsk1yY5PcWKXB3LMoSNQ6F465L81QSWsxkmqUUKablBYjpcXIaAnSWpyMnpzScn6chcrgdgjMcK9gX3C4ufsxjCcZK7JWMdu7mkbXcrb0P5NzCgtlutnc9wQnl12JVXIQTHcRTHcRzfqJZ4NEs34sopVza8ymg4yeJJSZmOxrOiFYLOa4GquNrt/eQ6Z3asci+3wFbScqSm7bVOsRuu/7jTmufJphnzmL6s/8A4ZhENuzm/DG9aRaBhud0p3teFadhvuksRsHDF1HEM0TLHnoIPH9+44Sawg1HEaLRoYrEQSB8mv+HjV6vGZpcqia5cRbZuWOXy9hza9aadkxWNcRBPjozfWcdlUVe17z54xtZp5cxJcfW0HLjjB//P5B+o5Mr9fHlHW6gfDYy1otGSfeeoj+jS8BIFoUlJJyvHOXoZRWYiutpGjxKRwbPt1081dJ9bST7Okg1dNBsnv8FjztaC5t/4Esr65L8c3vDZesVJRL9PYNkkF9nZzn3jURVNpn525bJQcnlV6Gy1KMIjnyimSFwsAgpUbNZbIWJqlGCKTaSWqRCeeLJwq7vfC567XOhbwX2TzqMY2V0xUFiUW+8xAQUCQHq8qv5pXOwSV5LBvgrd7H0Q31A4teC0XFtdejlJTR9dt7Jm13OBS22vpxtxEkiYpP3QRAsuU9eu77LXpmetMnzoWLzTE71TUEXn6R6JbNeX4Jx2CoKn2PP0Kmr5eSCy8hGwiQ7eslO+AnGwygBgOkWo8gFxVR+//MQltw3SsFqQokp5nG1KLToxrYs26Atfe1kYiofOJbs0lFVdb8qpUDbwW58a6FtO6K8B8ffztvyu87rw4w/4xiRFkY1QxnKiiYdBfNvppIrCvvh9XVuxVNH1smlQn2o/gG+8H1bIbUUUI9Hgu+9mM6n3uITLAfW3kNtspaqi76BNaSytwV09B10v4egrs2keppJ9XfhTqk8y2TNZAkaGqUcTgEZs20cPJyBZdL4PB7Kvf9IU4kqnPnFye3HLSI1lxEt2vgRXoSB5npXZVnsJ3W4sTVIP5UG0nVJNGhBHp+7Z1IgoWsnmJt568ndRzThXt/W3hhSRQkzqy8kXXdv8/lS22SC6vkRJEcuRTJitLLc9G+PIqqQBatw3LRKW16opsTjYEX/0LWP/l6wPGIvbOLskQC0eFAUBSModGrKFJx7fW5AlLLd/950o0H4+HYqJ1CEVq3ltC6taM+biktzd0uxMgIwHr0AjSdOuf9bwZp2Rnm9T8Mco4oCdz/leHpuFknF7HiY+X84KLNGCegGw0mQLrhWCft3ZsGnyhZC5KZG5qGZC98pLXsdJP295DsbiPZ3UZwx0YE2YKtvAZ7ZR22ylrslXVUnX+V+fq6nnfFj8UMTj/VSjCko+tw8FCWg4eyGIZpYv7VL7r5zr9ObGrtUDS6TY/UQLoz5yx2OPwWqp4mlOkhlh1A1T+8I9CnCllUWFV+dS5iHSkXXWKrG/d1DEMvuPj3YcN0Eu4x9D/3DBXX/D1GdjCIESSJ8muvx7XETGdlurumhXAtJSVI3iJktxvR5cJSXMLAcyPPnHPMX0Di3X2IViuWsnIkpxPR5cRW30Bw7StoY4ztEcQhRbMCi6uyxwtAdho9K/ztw1dOQyPbobDYRB7/wcETqsCbgGTMTV3VKgREDHQsspOsGudo5zrtPZsxRsktTqRAZnEPVyEYapZk1xGSXUdy9zlqZ2CrrMNeWYezfhZgp7FBprdPo7ZGpnaIZlwUobZG4o9PJvjOv4b52pc8/M/PIhM2MreIVhpcy9ANbVhu80h0xyjP+nDB6RRwOgT6+vUJyTt1Q8tF+G5L6Thbm/63STVKQg2RUMMMpNpYXnpp7vE9wdEjpP8/IrZjG2ha3iicyhtvxXF03E+6q5Pu306TQkIQMDSVZEszWjSK96yPAOBcvITEu/swhvSdW2tqUCor0dNpMj09ZINB9PZ2ZI93TMIFzB/eUYw3AusY5CIzZ62Gpq+jLh7KsuCsklENy4dC1wzmnDpCjt0ATTMY6EiN6uVQKAom3WDkCAPBg9RWrqQ/sB+HvZRQpG1Uos3byQQKZIWanic6Wkh0mFKZklPOoeLsyzjSqnLfH8wT5qzTraTSBm9vzXD+R20MBHRaWs3HHnwkzu23uPjlvROrTs5wn4wsKhwKbyKW/XD4HUwUPp/IVVfaufvnMQwDPnG1HV03AxHdMA0+XlmbHuZNkdXTeUVAMHWwkUw/Gd0s6lU75yMLCm90309SjeQVV5XjnjuQGt+4/MTDrCMcD8nuwF7TSOzw8WblAqLVip5O4Zo5n/iRQxja9OX8hhqdizZbHuF2/fYe9MT05Pezfj/4h9hT6jqyrxjZNzzg0ZJJIm9uMJ3D+vuwNc4wPW8LIVFxSL2gwNZduajIbHiaBncxgNOvrWb5heWjRraFQLGLNCz20Nuc4Nn/fu/9IV1ZsuG0lUDRbJyOClLpCGXF85BE08h83Oc7XQiiWFDPtK184m2Nhjq4JCvyiqQzBg6HwM//x8cpH+nlumucfOGrg19iT6/G+o1pli9V2LGrsFSAXXbT6Dbzas2R8U1tPqzo6NA4cFClskKip1fjxTUpRFFAkszARJZHNgPSjAxgEueB0AbaY+8M6zwrt89ElpScHGworOIg6RropLUTI8eZCGS3G8+8peiqilJcSrq3i/CebbhmLSDVPdJFwcC7+GSCWzdgragm1rz/hByX5HRRdevtAKQ7O+j63a+mjXBHglxSgnvlSoIvrRn+4FFydS5aBIKAUllFqvVIQa+bn14ojPQsxSWo4VBetD0VbH2+lzf/OPWJw54yhag/My1ph4JIV9VSdPt3UVm6mFi8m1Q6TCLpp6psKeFoG1l1nGqzIOJsnDtui2/XC48S2jPxsR1ayjwhLzrfxo5dWUJhnRdfTnHJhWnKy0Q6OtW8VIIgQG+fTl9/YfmFImsVp5ZfA8C7odfzRsf8LeLV19J85CyFnl6NeNxgzmyJq6+y092ts31Hhp6e4Z9LWkvkdLI62oRbfT3KYDE1mO6a8pyz0SAgYJc9OGUfLksxLkspNc75gKkSORBan0sFafEYuqoSO7wP18x5SHYHJad9FENTKT3zQjqfeTDvtcvPvYxUTyfexScT2LwO54w5ZIMDBZv1jwd70ywqP3UTosO8QDV/62vTRj5jQQ0GCb++DtFqBVFETw75PRuGmY7QdQRBINvXWzCBDtXsDn0fksuFFht+0RWtVmyNMwhvenPyb+Y4lNTY+PrTK2nfFyUWyBIdyBAdyBDxZ2jfGyPcnybUk0bNjP2bjvRPX52mINK124pJZyIYhoF4tAV4IHSYSKwTi8WJLNtIpUJj/pBEy/hSqskQLoB+tPjw4sv5Yb/XI9LeofHfP43yD7e5+On/Rs2ltEHBhCsgML/IzHn1J1tojZ6YWVfvF668wk5piciqVQq1tRKhkIGuQ3e3jiRDba3Ejp3DFSm6MfijESlQ3DsEypBId7xxPoXAZSnBJjmxSi7skhub7MYuuSm21o7aJSkgMK/oLFyWYvYE1oIo4ahvQotHQBAJ7Xo7V5QtXjn8XM4E/IgWC7aKGiSbHUSRxJHCPTfGgueUUym9/Kpcx1bojdfeF8IFMLLZo2mTwQGhx/Z9TGubOnyIdOcQeZwwvtRQGCGnKzmc1H/1mwy8+DyRzZvyCNxSZhqvZ3qmT4PddTDOn3/czMG3grhLFdwlFjwlCuWNDpZdUEZRhQ1PmUIqphLoSnFgU5D+1iTdh+P0HI6TTky/eVNBpJtMBairWkV792asiptZDRfQ69+DbqjYbcUIQDI1erWxd91zRA7smq5jHobR8mrH9LrRqM6998W5/GN2nnluYhrQetcSvEoFaS3OO4GXp3ysHzSeedZ8/80tKocOqyxcYGH/fpXLL7exbVuW9RvSWCwC2exxEzqGRPfCGOOGRoNVGmwjnyjpui2luCzFeX+fUfmpCR+DmdZI5AqBoiyTbG8mEwxgszmwllYgWm1YikauKwiSRHj3diSbg2w0jHvOIgTZgjFVvawgUPZ35krK0HX8f36ayFvDJx2cKMR2bMd79jlmesEwsNY3kGo+qizRdRBF0p2diFYrosNppsLFAi68Q7c5Sq5aIs7AX5+n7IqrcC9fQec9P89tcswxbTpJF6DvSIL2fYNyRE+ZwgWfbeCnnzJXPCW1Nmrmugj3Z5h7mo9ZK4s46/oaKpuc+DuSPPnvhzj41vSpKQoupHX37cLnnUEw3MK+w89QWbaU7r7CKvYDb4/exTQdGJrTHYrOrsGrVDSq8+zzEyNcm+RidtFqDAx2Dbz4oRftFwJZhoYGszFkwQILNptAcbGAIID1qKT2eMKF/IaHsWa8jYahRbiklk+6sqhgFZ3YZBdepQKb5M5FrzbJPaaD2PHIaAmSWoSkGiWlRUlqUULpHlJalIyWyFuNiVYb1rIqspEQokXBNWs+qd4uMAwCW4bbQYqyBfe8JWipJMmOFqIH3pmyu5fkdlNxrXkB0aJReh95kGTL+yul05NJYjt2UPKxSwm/+SZykTf3mFxcTNFHzsZQVfRMBiOTQYtFC4rCh0a6Qwtpkc0b0dMpyq/5e3znXkBo3VoMTcNaZ2p0xxvxM1EcX/iyOWWaThp8j+d/poH+9iS71/pp3T14blqsIhfd2ciyC8po3h4eNwVRKCbUBnzM2tEw9IIJ9/2AXuAybKK/jwW+c5AFhQOhDQTSY5sdf9hQYqsnpUaHDcucMUNmwXwLsgxnnK6w9tU0VVUS5WUSyWSGGz7t4ME/DC/aDDWxEQscXzMUI6UXPlJ1M4rkyLm1TQShTI/ZdHK08cRsQhn+fseC7HQT2r2FVHc7vpPPQEslSfd1Y6usZaiqQfGVItpspHo6kOwOrJW1uGbOz/m4AgS2rJ/wCWafPYeKa69HcrlJtbbQ89AD09aJNVFk+3oJvLQG7xln5uV0Y9u3kx3wD1MfiEeOjP+ieemF/OfHdm7HUFUqP3UTriXL6H/qcRyzjk6fmOZOu1BvmrJ6OxF/hnRCo78tSUnNoM9H294oNfNcw55nc8msuKSC752/adhjU8GU24A/DDC9F6YfiuTglc57PpBmB7P5wI5VcmIVnVglJx6lPNfpZZPcKJIDgbFza5qRZbv/uZxE69AhlUOHzIvUU08P/rjWrEmRVeHNjSO/16HFQ3kck6ORcKyQZqATTJuRzOvd91HrXMgC3zkk1BCRbD99yWYSaoikGiWrD36vC3xnU+9aCkB34gC7Bqbum2rxlZI4chD33MUYapZEx5G8VJVr9kJih/YOK5Rlw0GSXZPvmKq58wvY6hsB0OJxeh66n/ie3ZN+vemCkckQejVfPz3aSPRCPB/yzG9GEMXH9+ym78nHKL/6k9Tc+YWJHewEEAuYK2GrU6Kk1kZRhZVgd5pP/cd8fFVWiqtteCusSLLAY9811VjzTi8m3JuedsKFSZCu6HTgWLaA2JsfHtmUMdEuhwKxuffxE1ZlB5NYS20NuC2lKJIDq+gw/5ccuCwl4xJqIZAECytKL2fXwIv0Jkfvfc+Ou1gYPJbJ5HSPOYil1FjeZ9oR30tXYv+4pj1DZWhVjrnsHlgzpe9GtNpQYxHUeCx3/qT9vSAIFJVV4nOegezyEDs0vFV0suebIEkUnXW9yJgyAAAgAElEQVROjnATB/fT98SjaNNk7vJhw1DJ2GgttdGtbyN7iyg+/yJzuxNUPLS5ZPxtSSL9GboOxllybhmPfe/A0eMU+O8tZ3Lo7RD//KdTWPOrI+x4se+EdaVNmHS9F38EQbHABFQdosOO+7zTyXb2kNi+d9pd7g1dI7B9+keyTOVHLQlyLjI1o1PTo8CrVOQmLMiilZPLrpjycWb0JBktSVZP5f4ltSiqnkE3VHRDGzE6/eS1Dt59N0siaRCLGUQi+qgG5kMvAJNJLxzD8flcKMz0/Hjt71Qvhno6TaLVvAjFDu8bVNcYBv1vjB1Fp/09E96ftbae8quuQamqxshmGXjhOcKbTvwYoQ8UeYW00fOhwbUvoVRW4Vq8dOLG6AWirN6Ov21wZdc/5LahG4R60rTsDPPL23Zx8Z2NnP3pWp76z8N5Od7pwoRJN9vrx7503rD7bfOacJ19Kv5fDfe7LL39OqyzGhi4/6kTMlYkGwnS88rT0/66I0FAxGkpwiLaUUQ7imT+77aUYpUcpvmL6MibIzdZGBhktSQpPW5OQMj0k9YTR20dE0fJNjHpAl9DvcR7zSonnWQhEDAoLhY47VQrn71jeF50aPFMLNQPcgRYRBuSYCl4ntwxTPfEh+M70fRs4SmkiUS6ksOJ77wL8Z52ek5m1f6z/xl12T4eKr5+K/5fPoYWndznYV8yF7U/QLZ7uH+EpbYC9zmnEHjkL6BNvWgkDOlIG68xqv/JP2KrrSOy+cSoNlzF+UHHQGf+bybQlaJqppO9bwzw2PcOUNHk4BPfmsO+NwZ49f7p7Z6cMOlm2rtwf/Q0ACSfFy0YRvK6URrrkDxu7MsWkNyZ3z4peVx0f/9nqH0nqHV2ikRe6ZhNkVIFGAiICIKIJMhHrRotyKIVi2hFFq2Tsm4cCxktQTjbR0qLkdbipLUYKS1OJNM3rNo+HVi21ILbLbJ+Q5pwRGfLlgxnnqFw3/2mWL2ifOQodmixazz1Qp1r0VH/4GMjdwa9N9yWUlaVX81W/5/ITMC2cmhe/USmfKYTgixT/7V/QbSZqRU9mWTgr89NmnABlKY6rPObSLw9vhuYbX4TotuZt62eTuO7/lLiG3cieV1IXheW+iokjwu51Ee2px/RZkWPT4NSZwIdaXo6RdfvfzOlz2YsbPlz/pSJtj35KZ1Qb5rqOSbpAvQ2J8yo93ON0z6CbuKke6QTyetGdNhR6qrwfOZaBMXCwP1PEXnxdUS7jbLPfRrJ6yby8gasM2rp/v7Ppu+ITwB6EocoUqpyDmLjIaGGjkaaCTJakrSeIJrxk9WTZPQkaS2RVwQ6HhfUfh5RkEhrCV7rune63kZB2LlrMMLMZOCWm50sWWzhlptNHe3MmSOfEkNHB1XYZ3FR3T+Ouo+FvuHzy2LZgZwBe0qLUWFroj1e+FIyow8S9IfZ98K5YBG+8y7MaU7je98xrSDHIRP3uaciOu0mERYXIZcXY6kuw3/PH/NIUxCFgggXIPVuM4gi5V++EdHjpOd7v0QLhJE8TtKHW5F8HuQSH1JJEeE/vYrzlCWk9r03PYTLoHkNjL46sBS7yAbMC/7xn1HFpcvpX7MbPavhnFWJnslibygjsH7q7dfHTwJ+5FvDX1PXDP7ysxbmrS4GAfa/OT1+EAWTbvkXbiLb1Uv4r6+j9geQS30kd+8nuXs/jpMWUv7Fm4m+soHImvX0//Ihii4/j5KbrqL7u3dPy4GeaOwPvUFWTzHbexpZPUVcDRFKd+VIwoxCzX+aMbVk/7GOqQ+6nfj1N9K8957K7+8bXKr+4aGRo0+rNFxSMxRZPYUsWhEQOBjeeDRij5FSzf8nmk74W0TtF76SNxI9sX8fPX+4r6DnymXFqIEQmY4etEAEPRJDDQz3sNCiE/Rg0HX8v3wMz8Vnmn8bBkp9FRX/dAvZvgHU/iCpPYdAN5CKvWjB6cth2psGPaZHM7wpO38RXX8ceWR9ePsRyi9ZTv9Lu/EsrUf2OEj3han4+AoGXtuLGn1/BoHu3zi9o5gKIl3J68ZSXU5i5z6MdBrVH0QuKyHTZkp/Etv3Yl86H/vSBURfewsjkyX07MuoAyEqvvoZOr/xo2k96BOF9yJv0xbbPWaUOh0YLEp9cMtkSYLvfcfDW5szSCIMDOg8/GhixMYIyE8vxLIB2mK7SWtxItle0loC3dD4aPVtKJKD5sjk2rn/JiGKuBYupuic80zC1XVi7+wkuO7VCYn8g4+9UNB2emziuVw9lSb0zCsACHYb6ZZOer7/S/NBQUCprUAq8qDUlE+besCzajVKRVXu79GsHbseN2eXSXYFpdyDoWqkOs2aQqorSO9z23Avrkf2Ouj/607UeBotkcZQ/3b9T8YlXdFpp+TWa+j85l25q5U6EMRz8VkIikx8k9kkYaQzBB58mop/uo2+ux9Aj8WJrd8CuoEgSSdM1jXdONGEOzQfWqjH6HRixUkW5s61kEoaRKI6zc0q8+fLIMB551rRddMQZyxEsn20xYa3dY83Gfr/EkRFwX3yKrxnfARLsdk2HNrwOuE310+bLeFIOFZAk7wuLJVlWOfNILnjXTJthbXOWhuqsVSXU/WD/4fkdSE67WSOdKIGwiS2v4ulprzg1xoLsuc4O9ej57p7UR2eZQ2DxKkbCJKAntFQYymygRipriDWci/2+hKKVs6k/b7XcS+owb2kAe/yBjof2UiybXpMho6HgECJUInfGPwM5orLSZMibSQIGH2kmVr6ZfxIV9Pp/98H85YHWiBE5r02fFdfjFJTSfDpNejpDJbqCsJ/Xkv5F2+i/2cPoEVixN7ciu+6ywg++tyUDvT/CoZKrz6I9EK/X+fwe+aFpbZWYueuLLvfySKKpv2pbBlZGzzUxDw7ypDSybQH/y2i5KKP4Vm1GtFuTs1Id3YQ2byJyNvTL6RHErEvmo3odCAVubHObqD27n9GjyXI9g5gpNKE2wuXsMU378a2YCaRlzehBcJokdiwKpFcWoTqn5qJeOj1V/GcciqS22O+/tF9RPe0E91jqgFEi4Se1Ua0NbbVFpNsD2ApdqMlM2T8UbLBONG9HSeMcE0I1ItzcBs+WnRTEBA0+uk3OikTarAKNtLGCSZdPTU86lEDYaxzZtD5zbvwXX0xFV/7LNnOXpS6KkJ/ehktEqPk1mvw3/MweiqNpbwE66wG0ofHHzL5fx1Do8EPogrf1mauOBwOgUBQ5+KLbFgs5m/iN/eOvnQ9Et1Ok2clwKgSNWES7mPTDbvsodhaQ4mtHqvoYFdgzYRUEqNCELDPnIVn1Wpci5eiJxKEN24gunXztAynzNuVRUYu9WFfOhfRbiPd2onnkjNJH24j9spbBJ9YkyMx28KZI5bWPZecSeSF9Xn3OU5ZTGLrXvy/eQJEEcnrQmmswdpYg1TkRvJ5kIrcKPVVdHzlR1OSjemZDANr/kr51deO7I0iQN1nPkrrPS9TdHIT0T0daMlBhUp4Wwv2htIcweoZFUGRT3hGzkBnwOghaPQxS1zCe/o7SMgYGCSIIU9DE++kXiHT3k3JrdeYKYWHzdlK7vPPQPKYxZZMWxd9P/k9tnlNKA219N19P87TlqPUVRF9beSk+VioqJJY+1YFN37Cz7a3x9dTeotEJAkCA1OPJKtrJFZ/xMqZZ9s4/SwrhgEr509++SUOyY1OZXT6VJFIGDz0cOFkdDC8kWCmmxWlH8efGn7xFBBGjXRlUWFu0ZnsDUx+RM9QQreIVk4qvQyPUoZNGnsU1Eerb2OH//lJz2Nr+rcfYWgaiQPvEt+zm/4nHqX34Qcm9VojQbRZKbrqfBJb96L6g/iuvxT/rx8n292fp6VNbje9qC01FXkka51ZT2rv8PcWeWE95V+7BUGW6f2P3+C55CwSW/fivexsYuu2gADlX7mJ7m/9DM+FpxNbv43UXrNZpPq/vjwtOt3o1s1k+3txLVuRd79zViVKmZvWe0zXvtCWZiS7QuPnLqDt3lcxVI3is+ZjKXKAAWo0iaXIiZ5RyfijTLuGawiqhAZceGkzDmLBSqVQT5FQQooEClbsgouQMbVIe1KkqyeS6JF8E+Lo2o25FITs8+I651TCz7+K0mgOKYxv2kHp7dcRW7+l4Mmgx+ByCaiqwf59Y1fAfcUijU0yt33ORU2dzM3X+idMvLIsMHuuzJLlCrfc4SKZNNixNc2ra1Lc9e8ROtqmqFzISy/8behNj6E/2cLugTVEMsPlT2OlFlQ9Q51zEYFUO92Jg6NuJyDiVkqwHtP3Si7skodiW02eesImubHZRyZb3dBMd7GjLmOpoxMqjs32myi6f/9rUm2tJ6w9VU+lCTz8PACWukpsi2YhKBaM9PDgQrDIw5oaJN/oo7D6f/oHnKuWAGCdUUPkhTdQ+4No4SiSN//zE21W5IoSpCI3cllhI7OG4hs/r+WPv/DTsj8/9ZRqPZI3acJaVYTF5yC4Kd+HWEtm6H1uO9XXnErHQxsYWGcu7QVRwNFUgZbKoCUyxA50AQayy4YaG9xXdYPCktOcvPjY1CwYu41WooSYIS4gYUTpNloRBYksabKkSRpTn3gyuVhZ1ej/Rb6r/tCcrxoIEXvjbco+/2lCT/w1d39kzXpcZ6wkum5i0W5Nncze3VnisUGS+si5NsoqRKprJGrrZOobJWbPs9DXo1HfKLNhXZpCmoycLoFlKxQuvsxOZbVJHK0tKocPqlx7WT+h4PTmXfOW4B9AIW2q6EqMrJEspIi2sPhcwpneXEtvsbWWuUWnYxHtWERrzp+hEKh6Jjf0Mq4GSahhkmp42qdSJJvfP5tF99mnEHv1bfRRus2ssxtI7cs/Hrlk+FyzYzAyWWLrtyE6HbmOMPuyuVhqy5GLi7CUl1D5vTuxVJdjnTcDLRRBC0WJvTFxXxWbU+LrP6vlHy9vJp0c+TcjiAKy00ZoS/OIjyfb/HT9MT8vbugG8cM9xA/3YPE5KfnIfJQyD+HtLYS3teS2627L8MNHG3ntT+Fh+xfEsYcRO90S8ehgIBgzwqhGlmKxAgwzOIoZk58gfjwmRLqWqjLUQBgjnSHb48dSU4mRzqD6h1dr1f4AgQefofxLt9L1zf8GIHOkY1JdaY1NMnt250e5K05ROPMcK/veybJvT5bnnkmwYV2ar33bQ9MsC5+/NTCq/GkonE4Ru13gR/8aIRIe/GbqG2VOWqnw6kvTq2YQx8jpCpKMoWtgGHjr5hPpOoShacg2B7LdjShKJAZGzh/6mpYSbB5UFAiihGx3UdS4hHjfERL9J3YQ5Hj5XNXIIAsKi4sv4O2+JzEwCKQ72BNYy5KSC3GI3hGfl9VTBNIdpLUE9S4zaourQdZ3Pzji9n+rEB02HCsW0PVt09Tbdc4pxF57O28b+/L5EyLd3POWziV9yHRFE60KRiJNqusQ8Q3bUcNRsh3mCB5LbQXZzgKHTg6BIMKshTZ8ZTIfv7GYJ3418vL7GIGOBT07+io4G4zT8+zIFwTDgIO7kixc6WD7G/nR6Hfvred7t47sCldVr/DjZ5q453vdvPHcILGmSBA0+nAKHgb0HjxCMRHjfW6OcK4+iZKbriZzpIO+n/wePZmi7I6/Rypyk25uB103nYQ0zbyq6mbFUgtHKP/SLQz87nG0SAw9MfHK34yZEju3DZKuIMCPfxjhxz/M365plsyq1VY+fbW/IMIF6OvVeOXF4V/0xZfZ+fXPo8iyQHGJaEbVtRKz51r45U8m7wo1lJyGka4gUHvaFQQOb0e0KDSdfzPZeBg1GSObCOHfv3nU11VcxTScdS1aNg0IYOhkk1E8NXOJ9YwcWUwnxlMu9CWaqXbOw2etZoZnRW64ZzTrZ1PvY8z2nkaDaxltsV1Es35i2SAJNUhWNwu5FtGaI90PMhd+ouA+fzWRlzbmoly16zhvBEHAsXIRwaOpiGOQisbOaQM4ls8j/GdzkID/14+jJ8xAQnI7kcp8eC87G0tlKY5TFhN9dTPBR/4yoWNfdIoTX5lM26E0zz144uRy46G/MzuMcGHwGuJwiZTXKJTXWCirtrDoFAfzT3Lg8Ul86b+qeXdbgv6uQZ5JGoMrDgfjf86ForAZaYvmEN+4nfjG7Xn3d33nJ9T819fo+8nvp+2AjocgwIUfs/Pv3x7slHnyhTKuunjwpLztcy5e+FOSptkyf3fRcCOP8XDeRTYWLVUY6NcIBHTOPs+G1ysiCKCqBn29Gn29Gnt3Z3n5halFvkPJ6Xjy0NUs7RufQRBFbEXlhJp3kfB3YHG4sTg8Rycqj0w4oqyQiQUxDAPZ5sLi9GJxelHTCTLRE/9DOOacNhreCbxMqb0BRbQzx3s6pbZG3u57EjA/hwOhDRwI/W27blWXr0DVUqTSIZz2UlQ1TX+wsJbVbGcvia17kStLsTbVYZ1ZS9mXbiBw/7PE39pF+ZduIPjgn/OeY51VT7p17AYM28JZCFaFzFFZmZ5IodRXISgW0ofb0KJxRKuC55Kz6P7O/5Ltmpj3QVW9wg8fauTlJ0P89GtTU3FU1iv0tE3eu1pVRw603nkrzseuL6avK4u/O8verQniEY2/PBTgrMu8fP3uWv5u4btjBvhBw/xcZCyoTK27srAZaXtGKX4YBupACLnEhzowfTOEhmL+QgvxuMG5F9qYOUemaZZMY1P+Yb/wpyS/uK+EK86fnFnGKy+meOVFk0wdToFvfNfLnTcHRvwSBAFmzZGpqZPp79XY+87EvoD83OfI37Kh62QTUXxNSxEtVrLxEMlgD6KsIIgS2gim7bLNSbB5J2o6QeWyc2lZ+yB1p19F+5tPTej4JovxnMdqXQvRdJVjgX6xtWbM7f8W0dW3LXfbaS8lq42/qhMdNoquugC5ooTiT11Gpq2b5M79hP/yBnosiZHJYm2qQyr2ktiRP03bUl1upgPGgGP5fFL7W/Lus86dgfvcVUT+up7Y61sp/dx1DPzmiQkTLsC1ny8jldS5/0e94288BuYssfPfT8zgNz/o4S8PTy5IsDkHz0FBAMUmkk7qJGL6qAU2q1UgkzaG/dbtgjMv0j2GUqGKHmPyBvYwDZMjsp29KI2100q6d/yjm49eYKPIJ1JSKjLg1znzHCst76m88tcUF37Mnrd9Z4fGpg2Fj/ioa5Ap8omIojkzzGoVKC4VcThEVp6qoOtw1jlWrrvBgccr4i0y/xX5zPxvMKiTShpEIzo//a8IW94q/Oqcl14Ykt1318xGcRYxcGgrkmJDtjmJdr+HxeHBVTUL2WrHWlRO3zuvE3xv+KgkQRRzaQQtnUAQJURZwVU1Ez2bJuE/seOGjs/pCggUWasoszVSZp+RGwY5FKIg/Z9MFQBYFS8DodFN449BT6SQK0uIvfY2yd0HMTKDF/HIK5vQE0kqv3EbgfueGZZrVeqryLSPLF90rl5OfOMO7Mvm4b/nsbzHoi9vJLbubYpvvBzHSQsIPfkSie37Rnyd8fDRK73c/1+9hPyFqTsUm4ivVMJXbsFXJjN/uZ2yKgsLVzqQLQK3fbtywqTrcIlUNSjUNFr57LcrqW2yMnORjZBf5Qe3tZFOjR7CKlaRTGp4la1GaKLF2IfG4PkpI1Mu1tKjfcCkq/b6MTLTO87mvl/FEEXYvzfLaWdY2bcnyzOPm5rSZSsU2o4M/4I3rR+ZdGVZGLbssFrh7l/7iEQMQkGdaESnv0+jslri5FOs/OQ/I4RDOps2pInFDGJHzb1jMZ1RBg8XDEEYWTIW7TxE+aIzqVz6UVJhP86KGUTa9uIoqaFr6wtUn3wxWl8b4daRnbkEUcJeUkP5orNwlNZSt/pKZJsDi91N9n1QSQxNmywtuYhSW0OeGiGc6aU7cYCZnlW5QZOV9tmjqiE+zFAsLjLZ4blDUZCQZTuKxYnbWUVJ0WzczmpkSUESFVQ9w8GWv6Dp+auj/p/+AWOE0R16NI730rNJHWgh/Z5ZCJUrS1F7zEKVMquO6Lq3hz0PIL55F6Wf/QSS10X6yPBlv5FVSW5/l9J/uJZ0c4dpOD6O5+1I6D6S4c/3j06SK89x88nPlWJ3SVTVW1Bs+RfnSFAj5FdzxPjjfxo/RXHy2S4u/XQxFbUKJZUyTvfguWdziPR1ZHjliRD+nixl1Wbaa/WFHsqqzVxuRa2FilqFlx4PYlEEMiOQcpoUTeIiDAwO67vxCD5KhCoOajsL+lzGwpRJN7rurRFPmKkgnTZyxao7vuDmkQcGw/wlyxX27h6+pG8+lOWiS+3U1EnUNcg0NErMnGNhz64MX7w9SCYz+MEePqjy0VX5yyFFEXj8L2X8x3fDPPvENHQwjQJxjEJa3571yFYHvlkrUFMxBEnG6i2lbP5qXFUzURMRRFlBP67DR7JY0bIZkgOdtL7+KLWnXUH/3vV46hYQbN6JIIjIVgdqevrfl1VyUmZrpNIxJ3dflWNu7nZcDdIdP8DhiFkE9FmrqbDPAiCYmd6pr1OFRXagKC5kyYos2bDIdhz2UiyyA1EwfZZF0YKuq7R2bSCeHKwfVJUtp8hdRyoTIZ2JYrMWYbcVc7h1zbjR/Gi/H9vCWShNtfT//OHcfb5rLyK19z3iG3eY/rejpRc0HdviOaQPtQ5rdBBdDnzXXIR1biO9P/o9tkWzqPzW7Qz87qlx0xVD0TjXxq9/0DNiLrVhtpXWQ2m2vBbF7hK57vNl/Pn+AL2dZl51oC9LsE8l0Ge+90s/Xcw/fL+K5n3j10y2roux5FQnkYDGa8+m6WrNcOE1Pk46y8VXrhpeND7nCoV/uaeOVEKnuzVDV2uGdzbHSSV1fGUK6fTg5zNbXEq30Wr6LNBL3IiwQjqbHqM11xY8VQhjma4IgvCBC0l/eV8xd948eCV9ZVMFX/18kC99w8Pe3Rla3lNpO6LR2aHicovs3zu5JPfTL5ahG5CIG7hcAk63SGWViGFALGoQjxl4fQK7tmW5/YbJ+7mW2uo5uexKAHqT77HDn1+NdlfPQpQVQKBoxhLMvK+A1V3M4RfvRVeHrypqVl3GwMEtKA4P3oaFdG55AUNTMXSNqpMuoO+d14+qGiYPj6WMYlstJbZ6iq01IxbOVD1NT/IwewNrR9XKOmUfZ1bdAMCL7YXbflpEK+fW3AGYioc3ex4e5xkfHGbWn0d79yYMwyCrTu5CZ188h9S7zSM2ZUheN1X/9v8Y+N3TJHeOvVIQbApGKoO1qQ7n6mVk2ruJb9qVl8Y4BtHloOxz12Gb14TaH0AdCBN66iXSh4cvpxeudPBvDzRw5YJ3hz1md4g8uWc+P/x8OxteKMwq8jP/UsnHbyrm8jn7JqRYEwS468kmSqtk2g+naTuU5q+PBmk/PHi+n3NFEa89O7KXxK3frGTRSgdfutIka4/gw4aTsDGAgIBPKKfXaEdHo0acQb/eRYbxf0uGYYw64PBDPw14x9ZBkpkzz4LdIbB7R4YbPzFcC3jq6ZN7O0tPUviHmwN89ZseOto1XvpLkljMoKdLy5Oe/fgeHy/8aWpmF/lkNULPfN0Cena8jKFlcZTW0LdnPQjQePb1IxIumMW5VLCHVKiXoqZl6Nk01Ss/RnKgA32S+RBZtOJVyvEqFfiUasrsM0bczjB0+lNH6Erspy/ZPG5UF1eDpLQY8ewHJy06kbBZTd1sJmuuzqyKm3RmghJDQUB0O0ftgtPCUfrvfiiXchgLRiqD+/zVYBhEXnoTtW/0z12PJei96z68l51D9KU3c9KykXDLNyp56jcjBx+rL/LQ8m6KHRsKt6H0+CTCA9qE+4Wuur2UOUts/PP1R7ji5hKOHEjzi7/O5N1tSZ78VT9b1o3cQVZUKpOIaihWgfSQnG7aSFEtzsAiWPAJ5RzUdqFgTozp1FuoEhrpNo5M7CCPw/tCuoIsT7qNUtcHW63PvcjGKy+mRk09ebwTN1yZMVPmez/0cuWF/SSTBq0tKu8OiZZtdoGGGTJdHRpWq0BqjKR8IVAkR+720FWGs6IRLZPE6vahZUxi79u7nuqVH8NeXMWRdaNHdv3vmnOlhiobAoe2Ujp/NR2bnpnQ8QkInFV1U96kiNEQzvSyrf9PE57R5k+1ciQ6vBj4fwEN1WdwuPWl3N81FStpbn91Yi9iGMQ3jv35HB992twWPOVWXCVWvJVmoXnncx1UzvXQ/XL+3LHSRicDrfGRCU7TCT87tkfGGZd4KKmQeXyEJghZFrjmzlK+fWMr8UjhRVJvsUx4YGIcMXeZnU9/uZxH/7efPW8nuPr2Ul56PEjIr/LNX9Zx1WdLc6R7x3erKKmUKau2UFWv4PJKrH0qhKYbeTndNEkSxOjUW4gIQVyCl4DRSxVlZEkzYHRjQSHL5OtYE2cpQcgZ2xSKkluuRpAnZ/u3YpXC02vKuORyO393rYPnnx39B+50TWxk+Zz5Fn74kyK+8NlB5cWnbnHy20dKePz5MtbvqOSF18v50c98fPbzLqw2gVRyaqRrzmIzMXQJHu89QtXyC8jEB5dj7qrZWBxu/O9upHzhmSO+nigrpMNmblEUJQxdxVMzh1Sol1DLLmpWXZYbiFgIDIwxzWHSWoKW6HY29PyBTb2PTWoo5v7Q+g905I7T4ht/o0mgseZMevy70IbMc0umBijyNJyQ/Q2F4pBoWlWK4pTJpDQ694Y4+ep6FpxbOWzbRCjL6hvMqQ71Syf2WcgWgVu+XsFv/71nxKr/VbeXUttkpa9zYmm+kgo5l98tFF+/u5ZNayI8+jPz/Jdk8zx/+9Uo/3ZHW14qu3GelURU5+1Xo/z233v41g2t3H9XL1bbcPXCsbqLgo0asYk6cTYWwcpS6XRU1CkRLkwi0i2+/nLSh1qIbx5uYj0anKcsJfDwnzEmkd+686YAq8+y8m93FVFRKVFROfp1wu4onFyWLFe49R9c3HlzIM8U5+2NaV58PkVgQKOjLf9K/dDTpVOOdCvsM3O3jzdgaXvzSey+ShAEak65lORAF4O+Ns0AACAASURBVM2v3A+GQbhtL1UnXUjC345kdRA4ZHZ0FTUuJnDY1Icq7hKKZiwh2mWaicR6mrE4PMz/u68Q7z1C24YnCzrG/aE36Es2s7j4AuxHh0r2p47QEdtDX7Jlyj7Aqj61/HKhEBBQJAcl1jqcFh8uSwlepQKb5OK1rt9O+4ThYLiFcCxfmtfTv5ul865nb6KPrDo9s8dGQqQ3Re+hKFXzPKRjKum4hrvMyvrf519A65YWYXVa0DWDlZ+op6TBSflsN6IksOWJNrOrdBQ43RIfv6mYZEIn2K9yxiUeZi+y4yuXKS6XKa6wUNukjJo/HQu+cpnDewtvPJJlAX+vyv98pTMXsVuGeEFvXReju3WQHL9x3ZERX0dRBNLp/Pfcb5gKirDhZ0AbbFvuoQ2dqUscJ55eEAUkn9knX3TlBXgvOxd0nfjWd4i9sYXUvkPDnpLp6EEu9pKJT5x0BQGuv8nJE48kuOenUZYsV1i/o5Izlw/v4baMYsB9PJafrLBja4Z//Ozw/NaZ59g4ZbUVn09EsQok4gbJpMEzjycoK5cIBSZPOLKo5I1mN45z4dDSSWI9ppC9c3O+6buWSdG9fc2w1zxGuADJQBf7Hv9PACpnOek/kiDYvJNMcC/xoBl5eEoVIv7hV2pZEZl3RjH7Xh9A10xfhNe78zsN7W75hBuvO2QvimjHcnS0vSLacVlKsEnO3DZuS+mYgzELwTnVnyGjJdjqf5ZIZuJdjEPhddcRjrYPI1wwVw479z80pdcvBGUzXMw8tZRgZwJ3mZWK2S5a3g7gqbBRXOfg4HrzPbbvCrHqugYsVhGrQ8LfEmPnc52omfG/1/kr7Fx24/9H3nmHx1Febf83ZfuudlddsiRbsi3LveFKMcZ0Y8BgWggGUkhIyJsQAoFACilAkpdOIIEQWkIHYyCAAWNjwB3cm2xLsqzeVtv7zPfH2JLWu5JWcoHv++7r2svW7uy0nbnnec65z30y2fKFn9LRRiq3BLsSZede6eQn9xTy+xtqWffxwGLYOYU6HFkye7ek91BafEsuE2dZuGVRYtGHyZo4IKuv1q7z/OLEpK8ggM0hMXKCicIyAw3VifeDX9X2P0biyDvCsfFhGTDpxlraEa3aDeB+9xPc736CbkgexjEjcVx0JqGKMnyfb0wwtlH8QURT+g5SPXHz7RnE4/CPR7QTsXVThG9dnNpQo6csrC/0TM4dieXLQrzzZoDWFiXBAAe0cuNAYPAj3Z5txOH4do7obAqz8FflvP77PYyalYmzwEgsqlA0NoP//HJH8r5FFA7u8LL4f8fx7M2pu81OX1iQ5Na06t/pGekMtU5EJxoRBRlJkJFEHUbJhk7UoxONXW3uj9YIPRIPEFXDRJUwMSVCTAkTinuJKmHiapSYEiWuRogoQeJqbMDFGXJmBrGO7hCQfkg23o4UMitRxDJpOP6v9mKdNgrfxsrj6irXfsDPxjdqKR7vwKNC+Sm5vP/XnRhsOtpqEh8qSlxl5/ImMvKM6E1yWoQL2ujx6ul7kq4BR5bM9b/MY8VbnQMmXICcAo0U25r6D0lc/dNcRk4wcdfiZE/nzNxkRY0kCZy1yEHZGCOZuTqy8mScOXJCh5SsXJlJJ1vY/MWxnfn0hoGTbnsnpoJcoFtfGKmpJ1JTj+e9lWScfSrZ378SNRbD99lGAhu3ogSCiBZTX6vtFaPH6vjxdzoSkmcHD2jb/cktNv7zrL8rPOD1HD2J1VTF2L83ObYkCFqiLniUMd320EGyjJrHsNKX39xRIuSL8eHj1Vgz9QS9MWq3t9BWG+SUbxX1+p2AO8pX/+3bBWrNa/VEwwPf77ZwLZOzLsCqG5hXq4qKL9pOVAkRiWst7qNKiECsk6gSJqqEuv6NKeGj7tTcH+xnTE7I6pvHldL0+NKk5UwjhyDqtdvLUJxLtNmFaDIQ3HN83N4URSUWUSie6GTlk/vIHW6lfE4eAVeEA0f0bJN0ItYsA+7GEAH3wOKTqS7Z7/86n0hY5e93p982qCeyD5Fua2PfpHvlTTkYTAK//U4tSjzxPiytMJKZm0xn8bjKzq+CyDJUbgnQ2RbH1RbD1RqjZncIV1uMWJrmWMcKAybduMuNZOs9keb58DM8H36GnJuFZcYk8n/5Q5RIBME0cNK9+fYMfvK9jl5HsEteC/C3f2Xy3FN+Png3SFNDilGLKCb0aOoLsg5KhknMmG3AZBYoKJTIzBIpHirz8gt+BIGjTqTtcC3n5PxvIwnycSWIed8dis4oMmS0jdWvaDEqQRSSVGqSLDDn2hIknYDBJNFSHUBnFBk63s6+DYml3UdenJIsEO/FZORI+KMu1jS/zNjMMyg0V3S9r6ISink1P9y4h85wY3fLeyVANB78Zpm9C+B6bx0IArLdgpxtJ+5Lnhabx5fh36SF2pRwlHBtC/Z5U44p6Y6ZX8Ku9w+iKirOIWaKJzrY+UkTUy4uoqM2gNEis2t5MhGKokBmiQVnkZmgJ8ruFYP3TZh0soXTL7Tzu+/W4nNr99/lN2bz6hPpd1c4XDXW0+HrSMg6gZo9IdZ+lHokXb071KVUMFlErrstj3/d10w4qPDcX5r7JfQTiYGTbqcH0d476RpKi4nUNhBracf9znLc7ywn79YbBjTSzbCL3P1nO3t2xvpMXNXVxvnZD10892oWl15p5uc/SvZ/sJ42g8CGLShpxJNLy2QmTNJTMUaH16PSUB/H51X4akOE8RN1+H3KUc8QAzE3e91rqHCcSjh+9C70vWH50wdYcMsIXvnNborHaskwVUmmr3hM5ZOnDyBKAlanjlO+VcRZNwxj0wfJU2aTVeb060sQRQFThkw0qPDfh9M3+Y6rUba2L8MVbiBDl0utbwv+mOsb479gtOs5+YdjWHH/VpReWnyLZiOZF52MsbyYwLYqAtuSK6B0OQ4EWUSymhBkCSnDjKm8CDUawzx2GIEdNcdkf2d9bzS5oxysfGArnY1BckdYESWBz5+tYvrlQ3HVBzjv1tHUfNlB1fp2wj7tIR8Nx6nZ0I4xQ4c1S9/PVvrGTX8q5KPXO9mwopsM+yLPVMgr1hHwKXg7e78OYlG1V8I9jMd/rVU4Bv0KXlecB98q454fHaRuf3LiVpIE4vGv52GeNukW/ukWwntr6HxzWUrJmGg2YTl5Ks7Lzse/bjMdLyzpqnoJbt2NZE6PdA0Ggd//2cGTj3nZub3/H6+5Mc53r2rnxaU5XeEFQScjGo3EvT4Ujw/JZu2XdAUBzBaRZ5/08fpLycsaDAIXXWZO8c2B44B3E1nGYtpDx89YfPy8HHJLzeQMS9znI1ONcxYXozNIjJjuYNnj1Vicet76cyXRFHKgbZ+0Eo8qTLuogPqdXqo3D85N/6Avdcz460bIHcFeaOHSR09m6S1riASSZyKxDi+ud1aTddkcOj/QfA8kmxlBJ3fFem2zxqCEokh2K87zZ2CdVkFwz0H8m/enHBUPBrY8E86hVqaVlrPyga0MneJk/9o2YodCP4IENV920LzXS9gfS5iOCwhdo9y26qOLY8o6gSd/n2i6s/JtNwuuzeSd59IrgMkv0tN8cOAyrCM7QvSUqf3n4RbKxhh5eGkZj/+mkeVvJioqDCaB627L54UHWvok++MCVVV7fQGqbki+ar/gDBVtYqoC6pD7blNFi0nVFeSqxtHDVUGWEz4/8mWePEbN/v6VfS5zrF/2BWepGfPnqZLdplpmTz2h2+75Kh1+liqK3edHknTqxKnfU2XZ0Of3snJGq4AqCKI6suIiFVBl2XToc0EdUjwrYb0J59uuUwH1lKuKVEC1OHTqnMXFqj3PoDoLjEnLz1lcrJrtOjUjW69OPCdXHXNaVq/7deYNw1RAnX5xgWq0atu3Zem/tvN7rF/OoTb11s2L1Fs3L1InXT484TNDaYFqHqsdv3PBLO330R3xG4iiaijJVZ0LZqlShkV1zp+Z9N2E83nHZHXyFcMHtI96s6zetHKBeuvmReq4C5PXeSJeOr2gPrFsRK+f3/ZwkfrvdaPUzLy+uUGSBHVp5Rj1utvyBrwPj73Xfd4sNkn907+Tz0XJSIP6xvbRva7j8huz1f9WjVUfe2+4On6mZWDXirGo18/64tV+U8XR+ibc7yZW1MQ9PiRHBtHGFkK79idUmwkGPbYzZpH13cuRszXhtRIMDTqRNlgooTCe91dgnjoey7RJ2OfPw77gTOwXnIl5yjgEaXDFGgNFe9tuRo25tOvveDxKe9tuRLFv0+94TJsSiaKMTm8hM3sUYyd8i/LRCxlZcSFZOaNRlNQx4YBbe+Krh/6OhhWiIYV4VMXVGKJ4XHe1WcUpWVR92dn1HYCS8Rkpp50Vp2Sxf6M2YhAkAeVQPLdw1MCKZVJCEMhcuODo13MIutwcLFMmDvh73iZtluNrCbL5tcTQiam8iMCuWrIum4OxrIDMC2dT+PPLkDN7dBVQFHS5ToI7DyBZjVr8FwhXN2KdVoHjnGkJ6/z0wa2MmFvIiNML097HkxaXY3IY2PZWDdvfrhnwMR4LXP2zXGR94rxJEKFsjJEF12YyYabWTeKuJ0rQ6XuXchYM0yPLAnVVA9duN/XQ4fq9cfZvT55F1O4N8/AdicZKs8/pvv5ffaKNR+5oYFi5kfteHNbrtnSSEaPcfZ0LCORZRw54n2EwFWkcIl17cpmonOWk6P5fYTvzFFAU9MO0TLkSCiNaj83UPF0IogCKgveT1YR278P93+W43/kY97sfox9aRF9GP8cSHvdB2tt6moIItDRtwWTOIr9gCiPKL0hY3mDIoHTE2QwpmU356IsZXj4fnc6CKMqEwx4qdy1h7+6lBPx9a0sFobsQbcYlBWx4uxHx0K/tLDB2febriFC308uo2ZnojBKosOHtJi68ZQQzLi3EaNMiUMMm2ZH1AtVfaaQb6IxSOsWOJAuMmZONrO/7UrJOm9rn55LNSsbc0/pcpi+Yx41J+DvW3kHmooU4zjtrQOuJheOoikp7tbf7qYUWy1X8IVAU2l/7lMaH36Tj7dWEqhqIdXTHGi2TRhCpb0MJRhCNeuSsDESLEV2Og84P1tO5bEPC9qKhOG/+zxcsfGg2V/5zDnmj++55ZnIYmHZNOe4GP5/8NT2bQUEUGDIxi6yy/ku708HI8SYWfjeLB26pZ/wMC1felMMfnh3Kq5tH89DSMmadncGtl1WzepmHUZNM/PiPvT9QikdoNp+1ewdGuoIA2zYkhgFf/0cbo6ck80zP3mcAhaV6xs/o1n0ve8XFA7fWJykzBEHEcIhoi2zjMeu6fxurPhujPLgWPoNrwe7zIzm6f0Bdfg62M09GNOppuPN+4u7EgLcaiiBZLUeu5viip29tT72ZINC55IMTuistTVsByC+citVWSCTswWC04+48wIGaFQnLhsMe6g+uwWzOodNVhU5npqR0Lm0tO8jOGXPoEPovAtGbJGIRhakX5LPx7SaiIYVzbiymszlMXpmFqq868bVrhAvQtN/PFXdX8P5j1bQfDPLirxJt7ILeGDU9YrjbV7Qx6Zxcpi8sZPsnrf2qGESrhczLFtLx+lukykZaZ0wjfGDw5tDOi+YTbe8g2qhl69V4nEjtQYyjyskIhQnX1BKurklrXUpMTYrnWk8ahecz7XeUM21IdgtyhgVddmJDTf/mfZjKi1BCEaItnSihCNnfmkfr8x+Sc81ZtL34CWo8MYYYjyjsX9XI8NMKWPzimSz/62a+ejG1AfrJN45Bb5ZZ8rMviPhTOJDpRDIKLTiKLIyYU0D2CDu5FQ70Zhlfa5AnzhpY/7OeKB1tZEipnqt/movHFed7d+ZTMdlEwKewcaWXx+5sYOOnvi7PhQ9edjH7nAzOWuTgnefbObg3TOSI6q/ho42oChyoHBjpXvbD7CQHM48rzt/eK+bmhVV9an7XfezlxrsL2HZ1dzz7kyWdyHLifZVtHoYoyDT7KvFF2pEP+UADlGfPoS0wuN6DgyLduC+A3KMhXqyjk47/LE15MwGo0RjiAP0ajhZqONLtlNMDgl6nfXYCIIoSJnMOOXnjCAVdNDV8CWgVZCNGLSAUdBGNJCcyImEvIysuIidvPK72vV2Vaxn2YkZWXETA37/naTgQZ/2SxoQEyrsP9q40cDeHeeHWHQS9qUMWzfsT91NVVDa9n77UyLPyM/Jv+gE5132btudfTCAeQa/DOnMazY/9I+319YRks6HLy8VYVtpFugDRtnZEvR7/l5vI+9ENKAE/rqXvDZjcRZMB/+a9XdeSecJw4t4AcU+A9jc/S1o+Y85Emp/qJjf/l1q7q+Ceg0h2S0JxxWEsvWUNi/52CiXTc7Hm9B6Km3RZGZXL64n4YwyfU4At18SQydlk5JuxD7FgzTFqs7weCLojdNR4CbojCKLQZ6lvX7jwukzOvqzbq0GS4TfXH2DLan9KretXn/loqY9yYG+Y/dtD3PufYfz9d40c6DGqHTHBRH11uNe27alw1iIHi2/JSylL27cjyJ9fHsbtV9X0KhM7uC/cVZDREx++lqh+CkY9ZJuHUuacQWugGrshDwCzzsGOlg8IxQanPhqQn65l5mSMozXvAEEnI9msiBlWratohhU1GsO/djPhfTUEt1d2jXglu42s6y6l5ZHneiXm4wl9cSGRg1+XYbbA0NLTOVCtjWizsisoGnoKu7a/QiTcuwRm7ISrCYfceL0NmC3ZVO/7kGFlZ1JTtRxZ1jNs+Nns2/NOr9//psJ+1hlE6hsI7tR8YKUMGznfWUznu+8jWszo8/OR7BlIdjtyViaSxczBX/+h1/UJokjhr35B89+eJOZKzFDbZs/AWD6S1me1MlzRZMQ8biy+DV+mWlUXfr7+EqpXN7HkZ6v7XO54wFlixZxpoH5zsiHQ9OtGEWgPsefjeubeMoFAR5i2/R72r2okGjy+RSGHMVCp1ZHjntIKI/e+OIwdGwI8dHs9L39ZwaN3NvDBS+m1+3Jkyzy/ppyPX+/kkTtS39OOLJm7nylh+BgT773YwWtPtCUR8PiZFsxWMWUFnVWfhSzqiSphyhzT2edaA8Ck/Aup6lhLZ7gRVVVQUUFViCkRjhRj9uWne+xMzEUR2ZGBeeo49KVFGEePIHKgHt+qDQR3VCKIIkrw2NQu/98EUZQpGXY6NVUfA5BXMJkMezEBfyv1B9f0+j2Hs4xOVxVGo4P8IdNorF9PxdjLCPhb8fuaMFtyv7GkaygpRs48NCKSJUS9HsluRzSbkKxWRJMR0WpBdjhQIhEUr4+4z0fc6yPa0ori96MEgiihEEooRORg7y1crDNOQl9YQMeS5HNhHjcG26mzaX7in91vppj9HImvk3R7Q95oB1c/fwYPTHvz696Vo8bI8SbufXEYAW+crHwd35+7l4YD6c8+z73Kycevd/ZZSaY3CFx3Wx4XLM5EVeHRXzWwbV2gS5omSgL/+HgEPzpnH9Ejiq+GZ84iEtfixQXW0bT4tSKX4c7ZHPRsJqZEEAUJUZCwGfLY37GazlDiA+DEmJgrCrGOTjwfHWqjLYqYRo/AcspUFJ+fUGV1v6sYctVsGpdsQAl9c6pHUkEy6YkH07tIFCWGJBuQJB3xeBRVVdi7+22GFM+ibOS5VO1dRs+MjdmSg8mURWHRDPIKJne9X1B4EjX7P8LdqdWcjxg18Ex/xb1XsufOV5Kml/appSjBCN6dR9dC+zCizS3YTj8F2elECQZR/AGiTc1EOjqI+/wayXq9SSPTgUIQRTJOP5Xmvz3V9Z55wlgCWzVviZirE9FiRjSbME8Yh3XGNCSrhdZ/vUCkcXAlq18HDFYdF/5lJjVrBlE5JgAnfnLZJ/ZuC/LHH9Ry9zNDqdsfHhDhAmmNiiNhlSf/0MR//93B/G9ncvNftO7Tfk+cxtoIno44hUP1XPL9bF75W2JSen9H92DIrHNS0/klBsmCzZCLUc6gyrUWX+QorEn70+kei1fWtZeqzivm96vnHXP/t9Xxf/+uaihwHNX2BFlSzdMmHZN9T/Ua/osLBrT80FJN55xXMDnh/bKR56nZuWMT3rM7S9X8gimqLUPTANodQ1VBkFTQNL6HlxsxasGA93vGB7er2WeNT3rfVJylTnv7F2rO2ROO2zlL+o30upTvZy66WBUkKa11WGdOV50Lzuv6WzQYVOeC87v+lmxWteTPf1BL7vu9mnP9Nap1+lRVstn6Xe/P11+iLnxo9gk7F32+BNRLHz1ZvfLpOarBmvqc9fYyOQzq9a+frZaenP/1H0eK15wFdvWKH+WckG1NOdWqLr4lV73vxWHqC2tGqe/sHaP+t2qs+tbuMeqwUcna9cOviuzT1RGZJ6ujs89Qx+ScpQqCqI7KPr3f7fXFqyekc0T7c29gKCsh8+qL6FyyjLgndQDatWYvJd+by7hHr2Pfn97CvalmUNtTY3HkHM1YxXHJeSih0OFTgRIKE9yyk7hrcNVUANlnjqNjdSWu1ZV9Llcx7nJCgXZMlhxGVlyEu7Mm4fPqfR8k6XXdrmrcVDO09Ay8njqCwQ7GjL+SXdtfIR4/+hnAkKtm0758e8JoN3iwneDBdsp+fj7mYTkceLLvzgEDgamiHDUWJ7QvMYmXf9MPaHzgsaTlZaeT7MXfovWZF/pcryDLZMw9laaHH+96L2Pe6biXr8B+5lyMo0YiZzoRTUYO3Hx7kmLg/xacetM4jHYDr924ivyxmdSuT51EFWURS7YRa44Ra7YRa46J0fNLyB6RwaK/ncJHf/qKza8NLtt+vPDpO25sjhOjl//qMx9ffdbNO5IkkF2g0Z/f23sSL6ZE2dfxBQCjs+ehqgp72lZi0Wfijwyu5dQJ65EWrqolXNV31tizRZs6qzFl0IR7GIfLfgWdjNIRgngcNRZDjcaPinBtY7RpSv5FU/FuqyXm7T1OvXv7qynfN5oyyc2fSE7uOAD27n4Lj1srCc7Nn0AsGuJAtVaQEgl72bv7bfILp9BQtx5ZNjBy9EKUARKwbbzmbGbItZNz7kRa3kvUeLpWV2IZnoc+p3/tYeapFXi31RLt7N/PIlx7kJI//wH38pXE2juIdbiItXck6LyLfnsH3i/W4v54BbG2trTCDkMfuJdIXT32eXMJV9fgmH8OnhWrUAJB3B+vwP3xCgDybvpBF+HKWZlYZ0zDNnsGTY88QbRlcD66uRUO8sc4GTI5m/zRTt77zQaad6aXCAL4zpKzWfXwdvat7D25e9I15exdXs+6p3fz2aPbAbBkGbl186LuhVSIReI07XThbwvhawniaw3hbwvRccDL/k8bGTIxiw/u/pJtS6oHdazHA5bpUwjt3EPc5ydkyMJ+9ljcH65IuWz2d75NtK4ewWhECYUwjhxO+/MvE/cenW9JPK7SXNf/PXSYcAHag912koFoJyX2ydS6B9526qhJVzbriAWOTQz2MIHF/QNLuIlGHdaKQjybEz02RbOJ8P5aYm0doCiYJo7B9/n6o9rHvAVTUSIx9t//3z4Jty+Egh3UVq+gtnoFgiAkFGq0texCURLPp9mSQ0OdJqqPxcJU7lqC1VpA2hCg5LtzQYWqB9+jbfn2pEWUiEZMwdr+Y1WFl8+kURRo/zS5E2zSekOaPMj11rtHfKD2WCZEqKoHKaThRV/3mz8S69QentbpJxF3e/CtT1YlRJtbsJ08C8tJkxENBgLbd9D8j3+lRbiyQaL4pBzsQyw4iy04iq1kldpwDk18MF351Bze+vlqDqxLr335hmcrufiBWdRvbmf5XzbTsjv5IVM+bwgbX0icSZkcejY8X8meD+vwNgeJhmJc+tgpvHT9ypTbKZmuWbD6Wo9fx4rBILBlBxlzZuP+cAXR5hb8mxQESULOziTanPi7ROsbcX+4An1RIZG6BlCUoybcwaLF362dVlWFJt8ebPocvAM0wT9q0h0yp4wD7+852tVoOEw+avJHgiyic1rRZ1nRZ9uwjSvGkO/AVJSJcYgTBIENF9/flYQTTUYsM6egRmMIsoQg61HjcU3GlkYGOxX0ORlknlpBw8uribSk11q6PxypHjmScAE6XYnTwngsnBSq6AvZZ4zDWlFI/X++SEm40F1LovbW9fMQMk+twDIyH9v44rRIF0WhpxmyoNOR1FlUEFAHqGw5TLiixYz93DMTwgyCJGEoK8U0tgLzuDF4Wlppe/5FbQQtCOiH9F9yO/y0Am5etzDhvXhEwdMUYNuSajzNQbxNAbzNQW2U2Zr+/m9bWkMkEGP+PdNZ/OI8Nr2yn+V/7p55WLKN5JTbk76XkW+m8uN6Grd3T2s/f2w7U68eyZf/Se7YYs3RGgf4B7BvJwJqOIz7o5VINhvmqRMBFf2QQgJbthPrcHX5dAMgClhnT0dfmE+ksTklN3xdiMQDXSqHgSAt0s0ck0vHzuSneN6MYqxFR19aKMgScoYJa4V2M8gZJobeMA+d04KpNAd9phXZZup3BDT2ocVU3v0G4cZOFH8A32fryb7hajgkFlf8AaynTiewfvOg5GuFl81AkEUaXls34O9+XZCtRkq+fwYAdf/+vPcFD5/bPqrd7FOGMfxWrWzZNq54QPuR+/3rkLMy0eXn4Vu3cUDf7QuZCy/EvWw5cbf2EDQOLyXrW5cTbWklsHkbHdVLCWzpftDo8vOwn3k6rc/23l0ZINARpurzJmrXt+Bu8OOuD+BrCx6zm37PR3VEgzEWPjSbKVeNSCDdkWcMSanTtRdZ6KhJ1JXWbmjliqfmUDDOybK7vyQa6o5dHy6yOJEjXVHS2maFe7Fk1RcVoivMx1RRTsdrS/Gu/BzjiDLinR6C21M8xAUB3+r1XSNd2+knD2q/Ro7Ws3fXiSmK6g/9kq6klzBmmqlYPAVUFVdlGy0b6jA4jBjsRnY9kzilE2SJzJPLEfQygiAgyCJyhgnJpNdeZgOSxYAh345sNSLbTIjGxGSSnGEi/xLNGCTuCxF1BwnWdRBzICmNSAAAIABJREFUB4h5gsS8QUINLmLeEPFAmHggghKOEg9GUMKHnpKHjAbC+w/g+3Rt98pFETnbOWDS1WfbyDlvEqCZUg8W5uF5mEtzkC1GmpYeO/LpDUN/MA+dw0zcH05rdN8b5eaeP4lhPzobQdbOq7HQiWw1EvOldx69n63W4rmdbtRIhKLf3pHuIfQKY/kI9IUFBLZuxzH/HHTZWbQ+/xL1f/hz1zKCJCGajNrvLQhkXjQfw7Ch/a67cXsHH/zu+P4+VZ838e6v1rPgvhkJ75fPG0LN6mR5mKPIQsiTTByRQIzR55XQWulm3TPds05LthElrhJwnZhGoABnL7Bw0ZVWbryyF3mbIBDasw9Rr0cJBrGeMhPJasX9wccpF9cXD8E252RkpwNjRTmCXjeomeo9j2dzzfmNR92E4FigX9LNHJePqqpUvbWDgtlD0Vv1CJKIbVgmtR8mT2nUWLxr2pl1WgU550zEv6+JaIefgKuZqDtI1OUneLA96cQZ8uxMeu5GQnUdbPnek0d1YLHWdgS9Du/yI0Z3ipLQvy0dWEbkM+7RawGBXbe/RMb4EnSZFnRZVvROC7pMK5aRBeizrEgWQ7/rU0JRYr4QuedPouGVNbR9ktyz7GhhyLUz7vHrka3aFLNz4+Ay17axRQy/bQH6LBuNb66n/t+fo0QGUf0kCBgryjGWDsO9PDFpIuj6dlxLBclmQz+kkKbH/o4SCBLYmjpsosbj5Cy+lnD1AWyzptP40N+6RsWDRi83vXnSWAKbE3/LLsLvBXs+rGPPh90NLcddOIzcCgev3ZhYXmyy68kdldoM56n57zP6/JKkEEPOCDuNOzpA1dQNzmIroizQurf/RPI1P8ggv0jmr78eWIb+g7f8uDoUfnaXk4f+mJxc7Cp0kTXqiRw4SLzTQ9ZVl+J66z2UYPeoXJAkfKtWI5pNCLnZCJIIiopoMaP4BuYDPLRMx7Kvirl8XgPNDeldvznmUvKtFShqjKgSwhVqIBh1o5dMZJmG4jQV4Q41st+1Jqn/YV/ol3Rbv9JOUsU1k9nz4hbUQ83kOytbGXb+KGre6z2e275qN+2rdqe9M6mgc1ow5Gagz7VjyMlAn2fHmG9nz2/7bieeqivxYDH0xjNBEPBsq2XU7xYljcyPRKTVQ7jZjX9fM1GXj2iHn2inn6grQPBAK0r0+MuXRt61ENlqJB6MIJn0qAPcpqiXKb5uDvkLTwJBYOsPnyZYM/iuuY7zziLmcqP4fOiLu/u0SRk2dDnZA15f3OvFs2JVih0XteRkD4mYceRwjaAHQbhypgNdYT5ShhXRZkXU64jUNRLYlEzyhhGlBLbuIuOs0zSPg7hCtKmV4NadKdacGuXzhlC7viW5gKWoD8MoAWrWNFM8NQdzpgGT04DZaQABssoy+OEH52PNNSGIAvGowpond7HuX7uT+oz1xMv/8vLK8kKu/ZGd5x4fmNpn3aogj76QS2N9jFeeSQyH6IcUImdpUj5jxUhCu7X71PPJKkSrJYF01XicWLsLtbmVaHOrlkgbBHILJCJhlR9/qzltwgVoDVTTGtASvGXOmQSiri6ZWEfwIEUZ43GHmgZEuDCARNruF46QRqjQtLaW/JklNK0dvDuUZNKjc5jROS1kTB4GgC7Lypj/vRp9tg1Dfuqne/5FJ6U9PRfNJpTA4OJa2WeMxTa2iFBjJ5W/eR1jcSZj/vfbhOo7CDd2EmrqJNLsxru9jpLvzyVj0jD23/8ens01g9resYKlPJ/OdfsI1bvIv2QaSix90nWcVMbQH5+NscBBzBvi4NMrjopwgSRNruPseQDEPRp5KtGjV8DI2Vk4L5qPa+l/ibV1z2YESSJcVU2so3vkJcgy+sICwrV9d++I+wNI4TDRXU3E3B5QFOQsZ8pl3e9+jGg24Vm2UtufTAexjvSr7vRmmaEzc/nkr1u0vy0yJrsBc6aBEadrapWz75rSRapmpwFTpgGTvfeWO/GogrsxQP2WdgLtYdqrPYR9URzF1qT4cE9EoyqP3evivr/n0Noc4703Bt5h4ubfZNJwMMZnH/cg0miUcFUN0eYWdAX52E6bTaS+kXD1AVAUBJ2ckEiLtrSCIGAuKULQ6xEtZiSrBSUYIrA5vQ4ki66xse6zENs3DT7MEo75kIREuowqYXRS/zPbI5EW6TrKs/HVdjL2hun4Drq1XltxBefoXPa+shXJKBMP9f0E0WfZKP3pucg2I4JOQp9l0/4vJ4ujJZM+IVGjhLXpeNwf1l7BKNaKQiw78/Hv7b+c0zRxDP41fZucpIIu08rQG89CjSnsu3cp8WAEf2UTGy++P6VT02E/zoTs69eAomtOxbv9IHv/9FZXEk1Nk3SNQzIZ8u1TUBWVlvc3c/CZT4l5jm8ipuOtdwelJgEQDQbMkyZgnT4VJRik5Z/PdX0mSBJZV15K/e/vI++mH2CdOR3fWk0yKJrNGMtH9Eu6+pIhqJFognY4FZGKZhNqOELm5Qtof/41BL0O+4KzaX8utVY7FcpOLUA2SNRvauPSR0+m7NRkWeDERWVEAjGCrjDBzgid9X7aqzwEXWECnRHtfVeYgCvM994+lw3PVbLuX4ObbX7yfoDNG8Lc9Zcs2lvirPss/TzI+s9DTD/FyB8eyeGqsxporD/Un+2QVC/u82vyMEHAUDoU58L5CIJAcPdegtt3YRpdjr6kSFPTqCqxdheCTibu6iRa10Dcn95DwJklccX1GUTCKvMXWfnv64OTm0XifvRSoldvLB5CFo0DXle/pCvqRCyFGXRWthFqC1C1dCeCKCCIAq1bGvEdTG/qEWn3Uvv0Cir+dAX6bBtqLE6k3Ue0w0e0M6DFeevatUSZO0jMFyLmCRJu6uwKaQwG1lOmgyAMarRb9rPzkG1Gap/6BH9ldx+o3qzxBJ2WZDoR4YPekHveJIZcfTIbL30QJRLrCoWkG17ImjuGzg37qf3nCoIH0u/o2h8EnU6b8h+Wi/WwHzSNHkWkroG4x4Mgpzf5skyZiHnSBEyjyvFv2kz7y68Tbe3eX8lhJ/f6awjtryLm6qT1mRfI/9mPUXw+Att3IhoNiOb+jfXVUATBqEeyWRBtNqQMK6E9yRaZzkUXIMgS7v8uR9DrsM09GdcrS3FceDbeVeuId/Z/n5TPG4KnMUDbfg9Lf7GW+fdMp6Pag6cxyPTryrEPsfDgzCXEI9o5LJmWQ+2Gvmcg/qNULjx6j4unl+Rz399zmDs2/Z5+/37Sw/RTjETCKu2tfVx7qkq4qoZwVU3C28FdlQR39V3xmQ6+8xM7JrPAL77Xwl+fyqWqMsKurX2HAzIMeRRlTMAf7UBVFRQ1jknOQC+Z0EtmVFQUNY5Z5zg+kjElqlC/UkvCRAMRZLOOqE/b6XQJ9zCCB9rY8bPnMQ7JxLP1wIDlN/osK6aS7LSr1USLGTUex7/mS+wLzkIw6FH8ATzvp65+ORKO6cNp+2QHjW+kV1Ah6rTTme6o8lgj89QKSv/nHLzbDmpqBUA06PreJwEyZ48i56wJgFYcsefXr6W9TX1uBnFvqHcDoEMSNNFkIvPSi/Ct30hw1x4ka3eBQXh/NVlXX064qgbJbidcW5d6XYdXKctkXXkZ3s9XU//aX4h7E6fJ1uknYZk2hY4l7xCu0QpmInUNtD7zb3KuvZqOJW8TqWtAsqXj8aximTaJyMEGFI/mhpYqkeZ69W1M4ypQ43FM4yrwfvI5ajSGd+VqdAV5/ZKupBcpPTmfPR9qxBYLx1l6yyHjFQFO//kE2vZ5uggXYNLlw5l+7Shev6l3KaC//eg0utu+CvPpsgBzzjGTky/R2pTetb320yAHqqK886qPSOTrUQyUjtRx6TVWNm8Is+GLEE8+2Mlf/pHD4guacLX3fhx6yUxN50ZUFAREREEiILnIt5bji7QjCCIi2gzdJA9cMpt2TFcQBareSk4IyEaZWD+hhcNwTBtO8fVz2PbjZxIIV9TL6JwWzMPztPhuphWdw4I+04K5NBddpqWLPA5j3bn39bod0WJGX1SAflgRwR2VGEePxPfFBowjS/Gv29Sv5ESyGBj36HVsuvoxIu3pT0cksxZbiwdOrB7QOXMkI++6mPZVu1m/4K+oPdqH6xzaaC4e7BEzFQQyTxlF4RUzMQ/LpX3lTjzbajEWZdKxKo2Chx4o+e5c2j7ZQee61J0O9IX52vY9HlqfeQHRYKDg5zclGIkr4TCt/3oBBAHH+efQ9sJLfW5TjcWove2ulJ8Joohv/UZ865Pj/cEdu6i97S4km5Xie35HtCk91y7/+k2E99UkH1sPn2bL7GmEdlYSa+vQKiAB+7lzcX+wolevkZ44+9dT0ZtlVj2anKAbc14JeovMVy8nnuO3b12Ls9jKrZsXsfXNapb9PjmE1pyi2m2guPWGVv7yZE6fHgWpcNnc3hNfsiwwfqqBTeuOT+HGhZdbueuvWTz9iJt/3K+dgxef8vDGC17++WY+OzaHue9XqZUZbYHUJdN5lnI84cRrpiJ77oD3LW3SzRqXR9vW7vip3mYg4g1TOKeM2mXpTQMCVc2Yy3IZedfF6OxmdE4rOqcZyTywYHTzu33XOyv+AKE9+wnt2U/GuafjX7sJXVE+cm42tnmnEO/oTJl9BkCA4bcuQLYaibT7ECQRXZY1rQq0w/HpvmK6olGHIc9+TKfuI+9aSOPr6zj47KfJ2+sx0hV1Etlnjadg0QyMhU5CDS42XfM3oi4/hVfMHNS2Rb2MZOj9MorUN+L677Kuv5VwmJa/P42uIEUZs6rS/uKrKOHBJzz6q6gDiHt91P/+PizTpvSv+ezr4ZzRPVr3fvI5xooRyLlZhCurNZOlAWDEaQW07HUT6Eg+9rwxWuKuZyXaYbgOaoQejyYft6qoBDuPzQDgxX96CPgHN2I1mQWGDNUx+3Qjw4brKCvXM3yUDoNR4PuXNrFl47HVERcWy/z8d0727orw9MOJM4xwSOW2G1p5/t2CXkm3J4oyxiMgIggiVkMWAgJHGpYPFGmRbt70YgxOE8Y6N8ZsC0pUIaPUSd0n+3GMyKJ2Wf/rAIi6/KBC5smjut5TIjEi7T7ivhChxkMFD94QMW+QmFd7L+4LEfOGGHP/t9E5LBx8Or3wgJyTie/z9RjKhmpGKO98hHH0CEK7Uo/KAIoWn0bGxBJ2/fJFADImDaXs5vPZ/pNntf3vA6JOI93DMV3jECf67Az0uRkY8+wYCp1knTYaQRJofHMDdc9+etTx35yzJ1D96DJal21J+bl0KKarxOLkXzKN/ItOouPzPVSt3HlM/HMlsx7Z0Xf/O/eHia5l+mHFBLenTu74N29N+Nsyeyr+tZuSS4ePEtHWNjrf+7Df5WIuN5ZpE5NHuqKInJsNO/YgSBLOS+fj/ujTbjMlUQRZxlBWgqqoRGr6joca7Xq2La1J+Vn+aCfRYIy2fakf/PtWNrDljWQddqAjPOjWPEdi8/reiVEQwJEpkVcokVcgk1coMXm6kYIimYIiCWdWYrI84FdorIvR3BBj7GQDOzZHiPXTYy9diBLc/VA2sizw25vbU663sS7GnTe1MnWWkS/X9P5w1EsWYkoEX6QNRVUIRt2oqJRnnYooyICAw1gwYCJOi3QNThND5pSSNTaXli/r8dV7MOVYEEQBfUb6o1RVUVEOjbg2Xf0YMW8obaG9nGFC57QQburs10BcV1SAbc5MPB+sxHHxuQQ2bukys+45OjkSuedPouCSaez5zev4K7VRvW9PI/osG+W/vZRdt72o7a8goMswITstPcIgOcgZWtnluIevRXaYkUy9S3kKLp2O46Qy9v/lHfz7B2FODRQsmkH+wmlsujrZIvEweibSmt/fQsOr6/oe2UkDaxCtz7KhzxxY/zslGMRQVkKsw43ksBGp6T2GK2dnknnVRbhefRf1GMjKBgrNgL0V2+mzEkqkBZ2uK7SgxuN0vPo2ANbZJyFaLajhCLHmVlA1r4GeI+pFj53CJ/dvoaM6MRZ9YG2K60DQXM2ad3b2SqDv/3YjIbd2TxisukOSMu3am3H9KEwOAxmFZnJHOXj71rW07Dn6kIMowU/ucHLmfDNZuVJSU8dIRKWpLkbljggNdXHKx+i4+5Z2Wpvi+H3H9gHaEz+5w8nEkwz88bZ29h0q+73quxm89HTiA2v95yE+3lLMdRc2UncgNQdF4n6afN11CIGoJjmsdW8mFNN+O71kGvDIt1/SzZlciLXQRiwYRWfVYy/LxFmRQ8YwbcpT+VLqEVZ/GEisFMAyXGsKF6juXy8arWuk46WlmCeNIdbajhIIYRpZiuS0E9ycuvrLMX04Jd85nd13vYp3W/eoJO4LEarvwFpRyLhHr0ONxTGV5iY1/+sJQ4EDVVHxVzYSafMSdfmJdPiIuQMEa9uJ+cPEA2GUULS7bHmA0DktZEwoYcf/PNvnct3hBaXPh9Xh/TDkJRut9AX9oRF8f7DOmYkgSQg6GcFoQHJkENq2WzMgEsXukezh3vGH/lbDEdyrkjvonkiEdu8jtLv32VFP+Fb3rx3f/s4Brn35TL54Yicbnq9EVVXiEYW6r5JDTqUn56O3yLgb/BSMzyRrmA2jw4DJoT/0MpA5zNb1f1FKvC5P++n4hL+veOo0lty8mrovjy68pcThqQc7ueJ6GzX7YtTsi1JbHaXuQIy6A1G2bAgnPNt/dV8WbpdyXAkX4OrvZ7D0ZR9vv9LNLx1tcUZP0CepFr5cG+LBZ3P5zsVNeN3p79dhwgWIxAeuDum/Im1TA62bGhhx6ThCHQEaV9dSekEFEW+Yhs9q8DekX+Ej6uWuKbilPB+d3YLsMGvxXYcZ07AcLZHmsCDbzV3L9oR9yrCueGSfUBQCX3XHbSO1fU+lvTvr2bjooZSfebZqSSbPtoM0L92olTCnwJSXfoLOaWHjooeIp+lJMFhEXX72/KZ/lYFwaOTa3+yg6a2N2MYXk33GWKIuP/7Kxj5DH5JRh3VMEaJOIuu0CtpXlvdp6u5f+xWOhefi/egzdEPykfOyUeMKpvEVhPf3sORUVewLzsTz/krUaJRYeyfxTjeizYLiHbhA/5uI3csOsnvZQc7/4zR+8dWlAKx6ZHuCWc1hTFhYCoBslCianE17lYf2ai8BV5hgZzhlG3aAM26diLshkNJ9bLD4vLKEpa/4uP+3HSgKBPwqs4f3Xxg1YrSei6+y8sYL3j5VA0eDsnIdT72ez7zxB/F6Egl02VI/6w8MZcmLPu69o/ve/eUPWikdqePdtUWsXhHkzptaj3UUKyXSCi9IRhlPjQt9hoHsSQVUvb0Lc65lQIQLWh3/YYx75Lq0vhM7FM/tivP6QljHFvVPugNEXyR5OJYbaXX3SrjfREhmA7JNE2/3Jhkbfst8ah7/iHgwQtUD7yFbjBRcOn3A2yr5zum4N1b1Gi6ynjyNzjfeR19cgBqLIehkwnv2E21MnlIr/iCizYJxZCmR+iZ0Q/IxlA3F99k3393NkmUkGor1SoY9sez3X5I93E7eaAc1a1IX+bz/m43s/uAgez7qW0Z3JJxDbVSnMM0ZCAQBCopkRo7WUz5Gh94gcNliGzV7o7z2fPdoz5Ep4nErKL3w6UVXaOGnPTuOj6qnuFTm0X/n4e5Ukgi3J158KpmvqvdGuef2dv7wSDZeTxb33H787++0SFdvNWAfkUXYFcSUpWP4JWMxZpnZ9vja/r/cA94ddQSqWjCX5RJp99K2fAfBg+0owQhKKErU5SceiqKEosRDEUzFWRjy7On5th5PfA1t448F8i+a2vX/3kg3+6zxWMcUse/PS/FXNrHrjpco+e5cdJnWrlHykVDjCmosTjwYJbC/mWBtG/59zX3qk70r16AryMU0YTRKKIwSCKFEoihHmA+JJiOGkaUo/gByXjb+DVuwz5+H+93ULlTHC7JBwlFsxWTXIxsldCYZnUlCb5axZBvRm2X0Vh1Gmw6jTY8hQ0/uKDuyQcJd7+edX65LqTboiXhE4e1b17D45TN7lXZF/NE+CTerNAOTQ0/dpsRwQeZQK237Bqajrxinp7BYZshQmbnnmikr12G2JF4DS1/28ca/E2PRZ5xv4dR5Jn7141aCgcR7xWoTWXC5pe8CiaPAsBE6nng5D7dL4aare3/IhEMqtdWpcwLLlvqZNM3ApdfYuPeO9uN+u6dFusE2P1VLdzLysvG4KtuoeW8PIy8fjznPSqA5/disEolR+Yc3KfvZefj2NOI4qYyGl1b3OvW1Ty2l8IpZxP3hQbtk/f+MnnrhvkIFxiFOcs+bRM3+D1HjCrX/TE8dMiAoCtH6JuIVIwhu34Nl1pSUigQ5PwfvJ18Q3leDbd7JoCh4Pvx0QA8+S7aR0tn5CCKIkohslJB0IpJeRNaLml1phh7ZIKEzSRqpGmXMmQZ0JglJLzJsVh7ff+fctLcZC8cJe6MEOsIoMYWzfz2FVY9up/rzvsvUO+v8fHzvpkH79LZXe/jRxxfQUunm88e207TThd4i4yiy4m0eWLwxM1vi949ko9drceHG+hiffhhk21dhtm4M89Qb+TxyjyvpZ3vz314Ki2T+8Wo+N1/fkkCwC6+2YraIPHLP4PqJ9YWKcXoefj6Xxro4P722Gber91FuR3u8z0vowd+7mHCSgbsfyuaPt7Yf14KOtHW68VCsy/QmozSTli/rsQ/PIh6JE3al/+OGGzvZ9cuXsJTnU3j5TEbcfiF7fvdG0k0lSCK5509iz52v4tk2eEOd/5/R/M6XZJ81DsuI/ISCiSOhhKPU/O3Doyq3ThfeFavJ+eE1BLakTmjqCvOI1tajLyog1tKO9dQZxDpchHZUoisqIFrXmPJ7PeFvC4GqMu+Xk9GZUl/iSkwh7IsS8ccI+2NE/FFa9nQSCcSIBmNEg3GigRgBV7jr71hI+zfQGSYWjBMNxoiF40TD8aMyN9/536O7vp//1nIWPjSba16cx76VDVR/0ZRWy6MjsXplkF/e0MpFV1l58G5Xl18CQH6hzNuv+HpNOD12n4vb/5TJv97K56fXtlCzL4rBKHDl9RkcrI6x9OXezXUGi7+/ms/qFUHuvqWtV9P0dBGJqPzqR228tqKQUWP1PPeEm0+XBY9L4m9Q7Xo81dpTy71/8E8vf2UTLe9t1gzBDxGuIEvIVgOSxciIOy4kVO9Cl20l/+KTkO3dCTfZbsZcmtNnUYX7y2r23bs0bZPt4woBZJsJncOCeXgueqcVXbZVk1tl27BWFCZM5Vve20z1Ix8c9WZVRWX7Tc/inDUS367eE4lRd6BPUj4WsMycghqOENi8g9bHNVOazKsXEq46QHhfDbFW7VoKrN98qMWSnJD8tM07BTnLievVd9La3vZ3DrD9nQP9LzgIjBmto2KizJtvHZ8Y5RlzDaxeEyGUJpH4WoK88K3lCKLA2XdN4aw7pwx621+sCPLFiuRB1F+eymHx/L4fePfd2YEkw1/+kcuXa0Pc+AsHOzaH+eEVRxdb7glZFvjF3U7mnmfm9DHHdjB2oCrKhi9CTDvZyO8e6LYbbW2KE42qrPsslJCIGyyOazdgQRS0LhEFTmSb1iVCZzch20wYS7IxD8tBjcaY8OT3ka0GdCn0nhkTSlKuW40pXZ0jNOlVtEv3q8YVVEWl8IqZ1D698ngeYhehmktzu9QWJd85HcmkxzQ0u+sh0Vt8NBVyzh7Pgb9/PDiz8BRwrTl2GewjYRtfjH3yMEL1rl77r4GmXjgSnUs+0Ay+e8xyDlfzqbHEY/cu/zylI93XgT2VUZa8lkVxscTDjx77JonFQ2Se/aeVK789sBtcVVSW/eFLJJ2Io3hg2uk+96dUpmJc75rznojH4I4ftfJ5ZQmKok3bjxVy8iTueTyHWFTl6nP7n/EMBg/c3cGMU01U7owcKuCIH7PCjcM4atLNOq2CzNNGa3IwvYwu04pkOdSWp4/igCMRD4Tx7W7QiNQX0lQLvhDhJjdxf4iYL0zcd7g9Tzit9t9HC9lq1IoyDj0MbONKKDYbMZflonNqHsA6u6Wrhc1h5J4/KeFvNa4QdfmJeYIEa9uIeUNED7ce8gQJ1Xdox33oOL8uw5wjIZn02gzDYcY8LEc73iwb+mwr+pwMDHn2rs4UoDmUVT/yQdpNOwfq+vZNOS/xOLS0KDQ3H5/ZQVaWSH7+wIpUuqBqqois4Uffu/Aw5p1vYd/u9AtTImGNpGIxFbtzkMdxBGafbuKOezN55RkvL/7Tc9ykXfv3RNm/5/gW4Rw16bav2o1kMTL0h/OSTGlA04eGGlzEvUF0WTZ8O+sJN3Xir2rpsnWMdfpPuB2iIIkUXj4TXZYNUSci2y1IJh2SxYBsMWr/HqowOwzHtDIc08oS3osHwkRbg4QOtpMxeRiiTuLA3z8m0uolcKBV6+vmC32jupiKOgnZaUHv1Mp3ZZuJ0p+dd6hnnRFjUSZyRmqd9JFQFfVQmXYQ2aY1FN37xyXH+xC+dviDCpV7j49v8pQpOl55dfCWjPGokrKt+2Dx+fIA3/tp+kUzc84x88n7AQqLZB54Jpc7b2rj02VHN0i67iY7P766hdqqE1+VeKxxTMILLe9vxrO1lsxTyvHvbdKI1B0k5gkkkGnhFbNwzhpJ3fOfEWk/9oH1gUCNK7Sv2k3FvVdgyE2+oNS4oh2Ly6+9Ov3dvr+1bcTcgaRY6NRXf4qoM9G6bGu/xQhHDYFEpzajTmv8aTEgW41a48gMkzZSzTAhHxqtynZzwugUtBFt7rkTE96L+8OEWj1dxxmsbe9qDJowSm90fW0PFOdpY3Ct6rsVjj7Xrs00jvX1poJyqCxXrxeOWbZbrxOYNcPAHXcNTO51PLFvd5T/POWhrFxHVWXfpFdWruPuB7M5e9JBLDaRp17P477Hc/jT7e28+9rgQzE/vLzphBQunAgcs5huqL6Dhlf61u1aRw/BWlHI2AevYdPix7veFySRsQ8vZveUP0VTAAAYGklEQVTtL3clvoquPQ1LWW7qXmgCmIbmYCx0Uvbz85HMBvbc9Qrur2oGvM+bFz8xoO/0BfGQ25ZyIjpHqJofxYjbL8I+ZRigzSqiHX4iHV4CVa3EOv1EWjz4Kxu7moEe9tk9jBkf3E64xX1Mz0NvECRtRqHLtKLLsmEZU4Q+z4Gx0ImhOJtgdTOVP3827fVJZgNj/vkjPBv2aQ+ETj/B2lZinQFi7gBxfwjbxGG0fzS4UvWemDlDz7nnGPnd75NDJ5GISl6uxOxZepYsPTrT8D/9MYNH/ubl4MFvRijlMJ74aycfbS7mrEmpjXsKhsj84/U8gn6Vy+bWE4moRNrjLJrbwIgKHU++ns/YiXr++tuOXoso+sL/K4QLxzmR1hOSSd9FDgefX0XGhBKtbj83Q2u9MyKf8rsXsfMX/9Hc5Bs7GXLVbIqvm6PFEjMt2r+9xFHLfj6fTd/+24k6nJQQpEPWjidAegUQ8wTZfecrmMtyNSMg/4lrtd0fHLNGYZ81CsliQLIaMRZnI8iiFlJq8xLt8BLY20RwfxPtniBKKDJgH4p4KEJgTwN1/+jdLUw/QC+J3nD2mUa+d72FRx7z0dGR/Ps2t8S5/loLlyw0cdvtbhrTNPvuCVGEc882ctEl38yqR6UXw52ioVpFWGeHwv9c00znEedn3+4ov/heK39/JY+CYpk7f9x23D0Yvsk45qRryLNr09zDSSiHGeuoQkxDsxH12uaG/+KClN/1bKrpymQfHvEWXjkraTlVUfHva0KQJczDcoi6/FT+7o1jfSgDhiCJ2lT7RE63VZXAIF3Kjic611YiOyxaW6Y2D/7d9SjHOOSixhSEfuLO+rzUjU0HAodd5Jpvm7nvr96UhHsYl3+rnX895eSzlTnc/QcPL/xnYHHMGdP1tLYqVFV/vT32esO2r5J/v3GTDdz/dA7790S57YZWfL0YnX+1NoSqagmxZ9/J5xffbeXA/wPx2cHgmJPumAeuQZ/Vu1wl1OAiVNehZew9QWLeILnzJ2MuzaXu391tR9RDcqm651YR6fBrI6QOH5FDyTdUlfxLpjH0hnm0frgV/77+G1QeTwiiAMLxHeUanXmEXOkRrHP4ZFz7+zZ7P65QVdreT5aJHVPElX5lZMeCdG+52caatREee7zvmGQopHLt9S6efMLJ/X9x0NAYZ/kn6c8+LrzAxDvvptaVO+wieXkiJ03VUzpMpqRE4u4/eKhvODFhiPxCmfeXJB//Ey/n8drzXh67z9Vv2ODRe1z8z51OhpbpmDTd8LWTrl4wElG18y2jQ0FB4fifz2NOutt++E+G3ngWklFHoLqVYF07klFP6U/PJdLiYfv/PJdoLiMIFC0+rdf11b+0utfPDDmaLOZYdmEYLLq6RvQgXUEUkY1WdBYHOosdvdVB+641KPG+RzK5E+bSsjW5FFc2/p/2zjxKrrJK4L+3115dVb13p7N0J2RfCAkkyhJICARCAAE3NDiiIrI4ehCYQdQDjgrKKIpnxIkiIiIqq0IIAxgSSAIhrAmQpEknnaXTe1V17fXeN39UU51OV/WWTido/c555/Sr+u5bqqvuu9/97uICBqd0NefIhQwdrxjVAdQiB+7Z41A9DlSPI/Oax969b8c2tuSIzjF9msb559lYfM7gWtCn0oIvfbWdX/3Sh9vVN1zq0EYVNpuE2y1R5JWprVU5/zwbzz2f4L9u8+LzyUyaqFJcLBMIyMRigo4Oiw8+MOkMWgRDFiuW2/mfX3eNir9zwRk2nny4p8qbrktcd4uPW69v5YXVg7PoH7g3RM0EjQs/7WLLxmOftFSrzmBXeitxEUUgmK4t5K3UupxjS+QqWqzeCUZ16mz2mtuJi6HNaEZc6abDcerv6J01dNJf/x1hCXb+6Ik+1bycdWWZ0KxhTMn10oxiiR4PSvfD5Iduv5fm8FA+dympSCfJrg6SXZ2E9uzPKly7v5JYe+4eUq3b1ue0as3k4L+ox7L+7GiRPNiJrbqYsk8syFSgC8VI7Gsn8l4Us3sWdaTt4392VxHXXNdJW9vAmu2zn3bw7HNxmpstrrq6k7Fj+1rhbpfMtrfK0LRMnm5bm0Vzd62CaFRQ/0Gazk6L9m4FO3+ezlVfdrLg1OYjuo+hUlGl4vLIGDaJWNTi3ItdPPpgxtKtHKNy569L2PleatAK90PuuKUdMy1obDj2LhQNg4TIfD9M0iTJ/12Jii6maQvYltqYLVouMFHRgWOsdHshSdTdvILwtr28f+tfchYtGX9dpqjInkG24DkU97QxxPd3HBc+zZ7IhcwPKBUN0bgud73bstlnEmnOn8JopVOkIkFcFbUETpiPZaYRZhohLKLNpaSiISJNuxCiRxHIiopi2JFVHUW34yipoXzOYjSnF8XmJHLgA1q25u8a+1Gk48Vt/YaMSbKE6nXimVeXSbkuK8I2JkDwlR20rRk4ouGySxyctTS3hWsYfYsb3PFDLzfeDA88GCWVFuys76tYQmGL6vF9s6m2bytn1tyDxGI9vxG/X+a273o4Y/HgrOyR4OLL3XzrNj+/+XmQd7YkCHZa+AIKT/21ix//bylTZ+kUl2YeJja7zNIVTrZsjNNycHAP+XRa8KNbRr74zVCxSQ7eSvX+PZii5x4Ob8ETEUG2pjb0Gm8hiImhh8EdVaU7/tqlBE6bzKsX/DinwtVLPDjrykHQp3zjh21m8iHrKlqRo9+aAoejuN04Jp1AorGRZPPQFbVa5MMxeQqhjX1dHtnIhQHmepXzzyPY8A6R5r51AVSbC5uvDJuvDFf5BBqef4B4RxPpeGZaZw9UEWvLfb+CjFsCIUhGgiTDbbTv3EIqEkQMJ0bnKCOpCs6p1RjlRejlPlr/9hqp9vyxtJIiZzZNQTZ09BIPisuG4rahujOuBMVjx17THYvsdSAbGmY00R3ZEceKJEh1RLCNGdjlcMrJOrW1uf3FgYDM5BN6fz8XLtC5fGU7L/xjeBEkf3o41kvhAnz+cgebXkmO6sLaIw+E2b41yTuv976PzS/DY3/MKJjSCoVpswzmLrBx292ZGgUN9SleWRdn07oYr21IEI0c39EJtepMtqY2oqJhl1w4ZA9eOcAkdQ6qpBO0Wtln1mfHS8gE5HJarZ7ZqYyELtlwSB48so9d6dxFnA7nqCndMV84g9Jlswlv3YuVTKMVOai98YJMEZruKV/g9CkgQfjtRpItveMfc9VhOBS925+bae9CTveEbLPhmjUb2W5HKy4h1dJMvKEhp8JVHE4UtwvF40Xz+VCLfKh+Py1//lN2qp7u7MA5dVoepdvbvZCPtvdfoWzWIhTdTmjv4c0ZBZrTS9eBeroOZP7h3rHTUe1ODr7R/0xAmGn2bXwiu++rnUMyfGwtCvu4UlzTa5AdOkalH60ok0as+V1IqkJsV3MmgSaWJLB0Ngf//FLewjuyw2DcDSvwzK0lHYoS29mUSdIIRig+90Q6XniH0OZ6Wp/a0l3wPoo4gixHTZP4wY9yPwTa2iyeWRNH7u6ZduIcnVW/8jNl5vAWc30+mfvu79sV4ytXurjm6yNbrH8wHK5wD6f5gEnzgSgvrI7y218Emf9xG6cudnDeJU4uu8JNOi2454edrH8udswXy3JRqUyg0dxOjXICqqQTFSESIk6H1Ux9+q0+4ydrJ5FRuzKt1n6qlYnYJSdFcilxESMuIrSYgy8yP/JKV5IY97WzKTt/DuG3G7PJDanOKKnWMFPv/Czv3vwQqfYuAoumAtD6Qt8nhGtiOQBFJ03otlzsaN0WjOZ14KgtBcB3Sh11N15A/Y//3is3XzYMbOPHE35tM4rTSWDZ+XSu/Ufey3ZMnowWKCbRdACjZiztq5/G7OpuPldeQbIpMyVMteae6imuTMWzgaIXEsEWGtf/lTGnXoqVTtDVtCv7XjoeoWNn7xX/tvc3UTFvGUN1emesWwnV5kRzetBdPpJdnXkt5aNBvLGVwNLZaAE3oc07SR4MkmwJkWoNDbmYjxmOUf+dP6E49F7xyPYJZZScdxL773uBdPjI/LeHsm59/4rnG9/qJJ2Cjy0wWHWvj2uuH37a7bixCkvPtvHAH6Ls3dfzHW7YnR5S9MOxoK3F5OlHIzz9aARVlZi7wODUJQ6uv8XH9bf42Ls7zYa1MTa/FM/r/3W5ZUrKFcoqVXbtSHFw/8ha9mWVPWrOIwdIiBghq50QPUaJLtlwi9y9/t5LbUaXbFQo4wDYa2YKSNWps9hv1o98Y8qhMunbF+FbOImmxzez597neymh3b9+npn3fompP7mcnbc/irO2DCuRyulaKFowEYATbr+s70mEILq7leDrDdkUXdcJFYS39jxtRDqNbNjwfvw07OPHY8Xj+M9dhiTJRN97l9gH9b0OGd7yGgC2seMQZhpZ17PBI74zz+LgQw/2mxbzYePMgdwLICEskz1rH0JW87tQJFnJugUOvPpUv0csnXE6sqajaLaMn1cIFMOBs2wcZiJKOh7JuCjE6E75hGn1m7gw9AOKPgkg/kXT6dzwfi+FK6kKalGmU7NR6cOMJQm9OrjGkoOlvd1i2bk27rqjiK9e2zFstwLA62+kKCtVuPunRUSjgvt/H6W5xeTW7w2tHdaHuPUSYukQaStzTaqsoyl2KlxT+KAjd9ZofzL7w1t7NWPMRzqdKX+4aV2cZ5+IsGS5kzOXObj0824u/bybliaTfXvSRKMWui7hcsuMn6hh2CTMNGx9M8Gd327nYO715WFzxdWebDhbSiQIiZ7kE6fkJSKCKKhIksQkdS7N1h46rd7GlYSEOLzm9xBbr2cRQuTd6An1H3DznVIn5v7568JeExhw7KRbLxYnr75JnPz0jcI+Jvf4kiUzxMmrbxr0+bObJAnfWYtF8fIVInD+clH5latFyUWfEL7FS4R/yVLhX3qu8C89VxQtOlMY1WOycpKmieKLLhb2iZOEa+YsUXT6IlF51dcEIIovuDA77tC/D93mPny9OHn1TWLWqi/3e33jF68UIGX3XZV1fa4fELKq9Xo9MPkUoRiOAe9fkpXucyA8NVOF7vb3O/7k1TeJ2fd/deif83GwuWaMFTP+8HVRuXKRKFk+T/hOnSKM6oBQnLbsmNrvfWrEz7vqXp/4++PForxMGfFjl5UqYu1zJeIXPysSv1vlF5MmqkM+hk11iyr3dAEIRVKFSy8WEpKYVnL2oGSAQckMdTv7Aqf46e9KxYb6seInq0rFwjPs/Y7X3boom1ky4HGr5lUIV7kz/3F0SdzzYFnO98aqU4RdcmX3J2sn5f58JKeoViYKp+QRPrlUAGKiOifvOfvTqyNi6VavPI3is6bR8PPVxPYMnMK46+fP4Fs4idbnt+Zt9Njy7NvYqv1DvxghCL60HpFKIUwT76mnEVz34oBijomTUD1e9JJS9MpK2tesJvpu/8VUDqXhnjXU3bxiwGppbe9vonrhhezd8BgIgeH28+H6p7NsHEXjZ5CKdiHMFMlIkEjTLtLxLtreG1w/uoq5S2nakrEuQ3vepea0Sznw2jOkIrkLqGTqD4tB3+fxRNfbu9n6xXuw4rn9hkalD9fMsSN6zo8tMNi92+SqqztJjXCd1Yl1Kg/eH+Dhv0S5864wN3zDzZqnSnjksRh3/iQ86NRiS5hUeabjNkoQwiJpRrutsn66hxwiA5BIdw0oM1TWPBFhzRMRDJuUt9ODaldJx9LImowsS1TOq0BYgtDeMPHO3rOJMQuraHx5H4bXQGnOnySTTAoa8/RHS4oYqqRlVCVg5enpIyNTqlQjEOwzM7MmaTjtORgh90Jk+wH2//HlQfvpUh0R0uH4gAXGG+9bO6zrseKZeFbF48GoqKR4xUU9b0oSrU881sdVENm2lci2jG/Zf/ZSSJskWwYfG9m29l0Cp09Bcdv6HRdqzCyejVv0GZpe/z80Z0/GVORgA5GDDdl9W1EpgcnzMbwlWKkkB998AYSF7vaDEL0jICQJX+0cYu0HSMcjeMfNQHN4MJMxas/9Ejue/CVmoq9PremRV3FNqRz0fR5v5FO4ACXnn0TnAFXIBktxscx/3uTh5Pk6C08b+ZjZT3/SwXdu8fD9H/akD995V5jHn4xx938XsemlUlb9NsL3bh/Y5SCwaI7soKEz4zKTJQVdcWCJ/Ep7ODLDpb/WOhOXZUqnhvd1MeZjVex+sZGaU8fw+qq+C1zCEkz/1BTMlEm0pf9Y2Z99v/eCpCYZpESClEjilYqxyU5skhObZM8pr0s2QlZ7VuFC5jMaDiOidIfTmWDbN35Pqn2AGLcjMCRkw8C7YCHpjg7an30GAEnTM1EGufyukoTicqH5A2hl5RSdtZh0RzvB9esyERKDYNfdq3FOrBhwXKjxPaItjZTPXUrRuOlZy/Rw4p3NxN94HsgkW9Sc8SmsZIL2HZsJ79vea6zdX0n5nCXE2g9g85URbHiH8L7tWKkE5XNiecPG9j34Eo7xR5a1dTyiOA38S2ax44b7j+g4TqfEl7/o4oqVDn5zX4Qbbx75kosV5Qpf/IKT5Re1smNnb8Nl+440561o5YZvuvn6te5BKV1dcVDumozbKMMSJmkrQcqME0zkj674UMauFaHKBkkzOqDMSCMrEqqh8u4j2ymfU4rhMfBUe9BdGuMW1VD/zK7sWEeJg70b99P8TisnXFBHKtq/wXd4l2IbDlIkkJBxSG4iIkibFaTRfD+nfKfV0sfP65Dcw7vRkfLpHk+bbLcL31mLhaRpouqa60Rg2fnCf84y4T97qXBOm55TxqisEsUXXiTcc+eJ0ss+KVSvN/te2edWZv/O59Md9rVqxih8JtIonOPIN0mWhGNSpdAC7iHJKW67UNy9/YNllywQtd/95BFdj9cji43rS8UN33SLIq884verqZK4+iqX2PRSqVDVgccvOcs2qOM6NJ/wGGXCUJxiWsmSIckAwlDy+0eP5jZh8Vgx5eJJomJuuaiaVyGcpQ7hrnKLkim5131OvHKmAMSMz0w9ovMqDN1vDgiblH+NpT+9Kh2+IncoUmZR5yOF4nJnQ70AKv7tSsJbXsOMRLBiMSRFIb67IbewLGMbU0PRojNJ7N1L6OWXMKMRZLsdK5ZZHS9evoLWJx8fhTv56CGpCtVXnY3/zBmkQzHMUBQzkiAdiZNqDmZbLZmRBFYsSaotnOlxF0tixpLZXnfDQbbr1H7nMnbc9AAlK+bjnVfHzlseHNIxdE3iP25209lp8cST8aOWlHDHD7ysXZfgmTVx0iN8CkVSmV56DgkziiYb2DUv4URLxtq1Yln3QT4ZWVJQJJW0lczKtMcaCSWOfhryxGUTMLwGZtJE0RWS4SSpWJquAxFatvWk+pdMLaZqfjnpuImr3ImkSAR3h0iEk3Q1RTj4VnNG9R1DhBB5p8f/dEr3cIovuJDQpg3IhoHiciOpKl1v9U0BrfjClSBLRLZuJfL2m5iRnmB1xe3GfdI8otu24TllAa2P//O3o/koYlT4cJ84gYrPnkb9rQ8R3Xl0mhcez4wrmkdT13sk0l04dB9+ew2NwTcGLSMQOHU/keQxSKw5JMlp5uVTsQfsJLtSGG6djT/dnFNk1srp7PhbPdG2kYvRHgn6U7qjVsT8WKGVlGCMGYsVj2HFYyhG7rbtzQ8/hBnJ7WM2w2GC69dR/rkriNUfvc66BY6MxIEOpl59Dm3PvPEvqXC9RjmhRBOmSFHpnorHKMOlB3BqRUiSAgLebX2uj9yhMoqs4dT8CKyszPa2FzHFKGSWiYxf1+6389YD25h/7Vwa/rEHd4ULw2OQCPWOXqg5tZqm1w9ipiwmLa9jz/q9xDuOffWygfint3RtNTXE9xxSXObQ2npDRNYNJEPHDB/b/m4F8lN2yQJan95yXHXRGC0kSc4WQfLZqlFkFV1xsD88uAgOn62alBXDprppjTYcxSvNj3esh3Q0TdmsUtrrO1BtKrIioTk09r3S+0FaNa+Cfa9mXpNkiVkrp/Pm795BDJCKPxr8S7sXChT4V8Vnq8JQXTR1ZVbkZUnBUF3EUv1HYPhsVXTE92VldMWBJMkDyo0EulOjeGqAaEuMzoYgjhIHMz4zFZtX58XbNyAsgb/Oh7vKxe61ffu12f02Yu3H3totKN0CBQoUGEX6U7p9S9sXKFCgQIGjRkHpFihQoMAo0q97oUCBAgUKjCwFS7dAgQIFRpGC0i1QoECBUaSgdAsUKFBgFCko3QIFChQYRQpKt0CBAgVGkYLSLVCgQIFR5P8B1HDyz7/glugAAAAASUVORK5CYII=\n"
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "getWC(content)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2\n",
      "True\n"
     ]
    }
   ],
   "source": [
    "cip = [1, 3, 2,4 ,1]\n",
    "d = {\"hello\":1}\n",
    "print(cip.count(1))\n",
    "print(\"hello\" in d)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "outputs": [
    {
     "data": {
      "text/plain": "86"
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cpd = {}\n",
    "strArray = content.split(\" \")\n",
    "for sa in strArray:\n",
    "    if sa not in cpd:\n",
    "        cpd[sa] = strArray.count(sa)\n",
    "\n",
    "len(cpd)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "outputs": [
    {
     "data": {
      "text/plain": "<zip at 0x1c06bd005c8>"
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1 = SnowNLP(con[1])\n",
    "cut = \" \".join(s1.words)\n",
    "cut\n",
    "s1.tags"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('少爷', 'Bg')\n",
      "('好', 'a')\n",
      "('忙', 'a')\n",
      "('鸭', 'Ng')\n",
      "('。', 'w')\n",
      "('这个', 'r')\n",
      "('少女', 'n')\n",
      "('前线', 's')\n",
      "('嘉年华', 'o')\n",
      "('是', 'v')\n",
      "('五月', 't')\n",
      "('三号', 'Tg')\n",
      "('的', 'u')\n",
      "('，', 'w')\n",
      "('少爷', 'Tg')\n",
      "('在', 'p')\n",
      "('上海', 'ns')\n",
      "('那边', 's')\n",
      "('。', 'w')\n",
      "('五月', 't')\n",
      "('四号', 'Tg')\n",
      "('是', 'v')\n",
      "('深圳', 'ns')\n",
      "('初', 'f')\n",
      "('空动', 'c')\n",
      "('漫', 'v')\n",
      "('无限', 'vd')\n",
      "('幻想', 'v')\n",
      "('嘉年华', 'y')\n",
      "('，', 'w')\n",
      "('应该', 'v')\n",
      "('是', 'v')\n",
      "('一', 'm')\n",
      "('晚上', 't')\n",
      "('飞', 'v')\n",
      "('过去', 't')\n",
      "('的', 'u')\n",
      "('[', 'Tg')\n",
      "('笑', 'v')\n",
      "('哭', 'v')\n",
      "(']', 'w')\n",
      "('我', 'r')\n",
      "('昨天', 't')\n",
      "('也', 'd')\n",
      "('在', 'p')\n",
      "('深圳', 'ns')\n",
      "('的', 'u')\n",
      "('无限', 'vn')\n",
      "('幻想', 'n')\n",
      "('嘉年华', 'f')\n",
      "('，', 'w')\n",
      "('看到', 'v')\n",
      "('了', 'u')\n",
      "('少爷', 'Yg')\n",
      "('昨天', 't')\n",
      "('也', 'd')\n",
      "('算', 'v')\n",
      "('在', 'p')\n",
      "('漫展', 'Mg')\n",
      "('呆', 'v')\n",
      "('了', 'u')\n",
      "('一', 'm')\n",
      "('天', 'q')\n",
      "('，', 'w')\n",
      "('于是', 'c')\n",
      "('合', 'v')\n",
      "('了', 'u')\n",
      "('影', 'Ng')\n",
      "('签', 'v')\n",
      "('了', 'u')\n",
      "('名', 'q')\n",
      "('[', 'a')\n",
      "('星星', 'n')\n",
      "('眼', 'n')\n",
      "(']', 'w')\n",
      "('这', 'r')\n",
      "('期', 'q')\n",
      "('新', 'a')\n",
      "('视频', 'n')\n",
      "('出来', 'v')\n",
      "('的', 'u')\n",
      "('时候', 'n')\n",
      "('，', 'w')\n",
      "('少爷', 'ad')\n",
      "('估计', 'v')\n",
      "('八九', 'm')\n",
      "('不', 'd')\n",
      "('离', 'v')\n",
      "('十', 'm')\n",
      "('又', 'd')\n",
      "('飞', 'v')\n",
      "('回', 'v')\n",
      "('上海', 'ns')\n",
      "('去', 'v')\n",
      "('了', 'u')\n",
      "('吧', 'y')\n",
      "('[', 'w')\n",
      "('笑', 'v')\n",
      "('哭', 'v')\n",
      "(']', 'na')\n",
      "['少爷好忙鸭', '这个少女前线嘉年华是五月三号的', '少爷在上海那边', '五月四号是深圳初空动漫无限幻想嘉年华', '应该是一晚上飞过去的[笑哭]我昨天也在深圳的无限幻想嘉年华', '看到了少爷昨天也算在漫展呆了一天', '于是合了影签了名[星星眼]这期新视频出来的时候', '少爷估计八九不离十又飞回上海去了吧[笑哭]']\n"
     ]
    }
   ],
   "source": [
    "for t in s1.tags:\n",
    "    print(t)\n",
    "\n",
    "print(s1.sentences)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['少爷好忙鸭', '这个少女前线嘉年华是五月三号的', '少爷在上海那边', '五月四号是深圳初空动漫无限幻想嘉年华', '应该是一晚上飞过去的[笑哭]我昨天也在深圳的无限幻想嘉年华', '看到了少爷昨天也算在漫展呆了一天', '于是合了影签了名[星星眼]这期新视频出来的时候', '少爷估计八九不离十又飞回上海去了吧[笑哭]']\n",
      "0.9999999990847672\n"
     ]
    }
   ],
   "source": [
    "print(s1.sentences)\n",
    "print(s1.sentiments)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'con' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mNameError\u001B[0m                                 Traceback (most recent call last)",
      "\u001B[1;32m<ipython-input-1-39875224ada6>\u001B[0m in \u001B[0;36m<module>\u001B[1;34m\u001B[0m\n\u001B[1;32m----> 1\u001B[1;33m \u001B[1;32mfor\u001B[0m \u001B[0mc\u001B[0m \u001B[1;32min\u001B[0m \u001B[0mcon\u001B[0m\u001B[1;33m:\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0m\u001B[0;32m      2\u001B[0m     \u001B[0mprint\u001B[0m\u001B[1;33m(\u001B[0m\u001B[0mSnowNLP\u001B[0m\u001B[1;33m(\u001B[0m\u001B[0mc\u001B[0m\u001B[1;33m)\u001B[0m\u001B[1;33m.\u001B[0m\u001B[0msentiments\u001B[0m\u001B[1;33m,\u001B[0m \u001B[0mc\u001B[0m\u001B[1;33m)\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0;32m      3\u001B[0m \u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0;32m      4\u001B[0m \u001B[1;33m\u001B[0m\u001B[0m\n",
      "\u001B[1;31mNameError\u001B[0m: name 'con' is not defined"
     ]
    }
   ],
   "source": [
    "for c in con:\n",
    "    print(SnowNLP(c).sentiments, c)\n"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['唐探', '三', '就', '很烂', '，', '导演', '跳出', '来说', '观众', '不', '懂', '！', '都', '第三部', '了', '还要', '整', '谜语', '！']\n"
     ]
    },
    {
     "ename": "TypeError",
     "evalue": "__init__() takes 1 positional argument but 2 were given",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mTypeError\u001B[0m                                 Traceback (most recent call last)",
      "\u001B[1;32m<ipython-input-6-f5fccaaa2d67>\u001B[0m in \u001B[0;36m<module>\u001B[1;34m\u001B[0m\n\u001B[0;32m      4\u001B[0m \u001B[0mprint\u001B[0m\u001B[1;33m(\u001B[0m\u001B[0mcut\u001B[0m\u001B[1;33m)\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0;32m      5\u001B[0m \u001B[0mc\u001B[0m \u001B[1;33m=\u001B[0m \u001B[1;34m\" \"\u001B[0m\u001B[1;33m.\u001B[0m\u001B[0mjoin\u001B[0m\u001B[1;33m(\u001B[0m\u001B[0mcut\u001B[0m\u001B[1;33m)\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[1;32m----> 6\u001B[1;33m \u001B[0ms\u001B[0m \u001B[1;33m=\u001B[0m \u001B[0msentiment\u001B[0m\u001B[1;33m.\u001B[0m\u001B[0mSentiment\u001B[0m\u001B[1;33m(\u001B[0m\u001B[0mc\u001B[0m\u001B[1;33m)\u001B[0m\u001B[1;33m\u001B[0m\u001B[1;33m\u001B[0m\u001B[0m\n\u001B[0m",
      "\u001B[1;31mTypeError\u001B[0m: __init__() takes 1 positional argument but 2 were given"
     ]
    }
   ],
   "source": [
    "from snownlp import sentiment\n",
    "\n",
    "cut = jieba.lcut('唐探三就很烂，导演跳出来说观众不懂！都第三部了还要整谜语！')\n",
    "print(cut)\n",
    "c = \" \".join(cut)\n",
    "s = sentiment.Sentiment(c)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
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